High-accuracy immunochromatography concentration detection method and application thereof

Abstract

The invention relates to the technical field of biological detection instruments, in particular to a high-accuracy immunochromatography concentration detection method and application, and the high-accuracy immunochromatography concentration detection method comprises the following steps: forming a combined sample group by using a calibration sample group with known concentration and a to-be-detected sample with unknown concentration; obtaining a visible light detection result, a fluorescence detection result and an infrared detection result of the combined sample group; obtaining a standardized combined sample group; obtaining a main component sample group; fitting the sample data of the calibration sample group with known concentration to obtain a fitting curve; and substituting the sample data of a to-be-detected sample group with unknown concentration into the fitted curve to obtain the comprehensive concentration of the to-be-detected sample group. The defect that the accuracy of the concentration detected by a traditional immunochromatography detection method is poor is overcome, the method is more sensitive to recognition of the to-be-detected sample, the calculated concentration value is more accurate and effective, and the method has more advantages especially in quantitative analysis of the low-concentration to-be-detected sample.

Description

Technical Field

[0001] This application relates to the technical field of biological detection instruments, and particularly to a high-accuracy immunochromatographic concentration detection method and its application. Background Art

[0002] Immunochromatography is a technique used to detect specific antigens or antibodies, commonly used in rapid diagnostic tests. This method combines the advantages of immunological techniques and chromatography techniques, and can provide results within a few minutes, making it very suitable for point-of-care testing. Immunochromatography can provide results within a few minutes and is very suitable for point-of-care testing in scenarios such as food safety, environmental monitoring, and medical diagnosis.

[0003] Currently, the main pain points in immunochromatographic detection are the limitations of the single signal mode. Traditional immunochromatography usually only provides a single colorimetric signal. The quantification effect of a single color signal in diverse samples is limited, making it difficult to meet the requirements of quantitative analysis. Moreover, the single colorimetric signal is easily interfered with, resulting in low concentration accuracy in detection and poor accuracy in quantitative detection. Summary of the Invention

[0004] Based on this, the object of the present invention is to overcome the deficiency of poor concentration accuracy detected by traditional immunochromatographic detection methods, and provide a high-accuracy immunochromatographic concentration detection method and its application. The present invention is more sensitive to the identification of samples to be tested, and the calculated concentration values are more accurate and effective, especially having advantages in the quantitative analysis of samples to be tested with low concentrations.

[0005] To solve the above technical problems, the present invention provides a high-accuracy immunochromatographic concentration detection method, which specifically includes the following steps:

[0006] Combine a calibration sample group with known concentrations and a sample to be tested with an unknown concentration to form a combined sample group;

[0007] Irradiate the combined sample group with visible light, capture the color development strip to collect the colorimetric signal of the calibration sample group, and obtain the visible light detection result;

[0008] Irradiate the combined sample group with an excitation light source of a specific wavelength, filter the light, and collect the fluorescence labeling reaction intensity to obtain the fluorescence detection result;

[0009] Heat the combined sample group with a laser, perform pseudo-color imaging on the photothermal response in the combined sample group, and collect the thermal signal output to obtain the infrared detection result;

[0010] Standardize the visible light detection result, fluorescence detection result, and infrared detection result of the combined sample group to obtain a standardized combined sample group;

[0011] Calculate the covariance matrix for the standardized combined sample group to obtain the principal component sample group;

[0012] Fit the sample data of the calibration sample group with known concentrations in the main component sample group to obtain a fitting curve;

[0013] Substitute the sample data of the test sample group with unknown concentrations in the main component sample group into the fitting curve to obtain the comprehensive concentration of the test sample group.

[0014] In the present invention, by processing the data of the test sample and the calibration sample group, a combined sample group is established. By analyzing the main components within the combined sample group and using the principal component analysis method, a main component sample group is obtained. A data fitting curve of the main component sample group is established. Based on the fitting curve, the concentration of the test sample group with unknown concentration is calculated. The calculated concentration value is more accurate and effective. The present invention analyzes and identifies by covering three signals, combines three analytical detection modes of visible light, fluorescence, and photothermal signals to comprehensively achieve quantitative analysis. In addition to the basic visible light determination, the double spectral overlap of the fluorescence signal improves the sensitivity of the fluorescence signal detection. The photothermal response provides a stable infrared signal output. The data are mutually compared and demonstrated. At the same time, there is also an infrared photothermal signal as a third comparison means, further increasing the comparison samples, significantly improving the accuracy of quantitative detection; The present invention sets three signal identifications and uses the principal component analysis method to establish a fitting curve, making the identification of the test sample more sensitive, especially having an advantage in the quantitative analysis of test samples with low concentrations. In the quantitative analysis of test samples with normal concentrations, due to multi-modal detection and data fitting processing, the experimental results are more reliable and accurate, and it is particularly suitable for scenarios where the actual sample concentration distribution is wide and the response is uneven.

[0015] Further, the method for obtaining the visible light detection result is as follows:

[0016] Irradiate the test sample with visible light, collect the image information of the color development strip of the test sample through an industrial camera to obtain a colorimetric signal, convert the RGB image of the colorimetric signal to the CIE Lab uniform color space through color space conversion, and construct a color difference gray distribution matrix;

[0017] Specifically, taking the standard black (L* = 0, a* = 0, b* = 0) as the reference color, based on the color difference formula △E = [(△L*)^2+(△a*)^2+(△b*)^2], calculate the color difference value △E00 between each pixel point in the detection area and the reference color pixel by pixel, and construct a color difference gray distribution matrix, where the color difference value is positively correlated with the gray value.

[0018] Perform projection integration on the color difference gray matrix in the horizontal direction to obtain the horizontal cumulative color difference distribution curve of the test sample;

[0019] According to the difference in optical properties between the sample reaction area and the substrate material, the local minimum point of the cumulative color difference distribution curve is detected to achieve accurate positioning and quantitative analysis of the test line and the control line to obtain visible light detection results.

[0020] Since the detection line and control line (T / C line) in the test paper reaction area have different optical properties from the base material, that is, the normal base area has a large cumulative color difference due to its high reflectivity, while the immune reaction line area has a significantly reduced cumulative color difference due to the light absorption enhancement effect produced by the aggregation of nanomaterials. The present invention realizes the precise positioning and quantitative analysis of the detection line and the control line by detecting the local minimum point of the cumulative color difference curve, which effectively improves the objectivity and repeatability of the test paper strip detection of the sample to be tested, and provides a reliable image processing solution for instant detection equipment.

[0021] Furthermore, the method for obtaining the fluorescence detection result is:

[0022] An excitation light source with a specific wavelength is used to illuminate the sample to be tested, a filter is used to filter out short-wavelength stray light, and an industrial camera is used to collect the fluorescence marker reaction intensity to obtain a fluorescence distribution image of the sample to be tested;

[0023] Specifically, a 365-370nm ultraviolet light source is used, and a 450nm long-pass filter is used to effectively filter out short-wavelength stray light, retaining the fluorescence emission signal >450nm. Image acquisition can use an industrial camera in conjunction with an optical imaging component to obtain the fluorescence distribution image of the test strip of the sample to be tested.

[0024] The fluorescence distribution image is converted into RGB color space. Based on the spectral response characteristics of the fluorescence signal in the long wavelength region, the R channel data is preferentially extracted to generate a grayscale distribution matrix. The grayscale distribution matrix is projected and integrated in the horizontal direction to construct the axial fluorescence intensity distribution curve of the sample. The extreme value detection algorithm is used to accurately locate the characteristic peaks of the sample reaction area detection line and the control line, and quantitative analysis is performed to obtain the fluorescence detection results.

[0025] The present invention significantly improves the signal-to-noise ratio and positioning accuracy of weak fluorescence signals through a strategy combining spectral filtering and spatial integration.

[0026] Furthermore, the method for obtaining the infrared detection result is:

[0027] The laser is used to preheat the sample to be tested spatially and selectively and to achieve targeted thermal excitation. After thermal equilibrium, the thermal imaging technology is used to collect the panoramic thermal distribution data of the color development area of the sample to be tested and obtain a two-dimensional temperature field matrix.

[0028] Implement multi-scale extreme value search in the color feature area and use dynamic threshold segmentation method to delineate the effective detection area;

[0029] Locate the extreme points of the temperature field through the gradient tracking method to obtain the infrared detection results.

[0030] Further, the method for obtaining the standardized combined sample group is as follows:

[0031] Calculate the mean and standard deviation of the visible light detection results, fluorescence detection results, and infrared detection results in the combined sample group respectively;

[0032] Standardize the visible light detection results, fluorescence detection results, and infrared detection results of the combined sample group according to the mean and standard deviation:

[0033] z = (C - u) / v,

[0034] where z is the standardized concentration of the sample to be measured, C is the direct measurement value of the combined sample group, u is the mean calculated from the combined sample group, and v is the standard deviation calculated from the combined sample group.

[0035] It should be noted that C is the direct measurement value of the combined sample group. For visible light detection and fluorescence detection, the direct measurement value C is the integral of gray pixel values or the ratio of the integral of gray pixel values of the detection line and the control line; for photothermal detection, C is the temperature value.

[0036] Further, the method for obtaining the principal component sample group is as follows:

[0037] Take the eigenvector corresponding to the largest eigenvalue of the covariance matrix, and perform a cross product of the eigenvector with the detection values of the visible light detection results, fluorescence detection results, and infrared detection results in the standardized sample group, which is denoted as the principal component sample data;

[0038] Perform a cross product of each group of detection values in the standardized combined sample group with the eigenvector, and form all the obtained principal component sample data into the principal component sample group.

[0039] Further, the method for establishing the fitting curve is as follows:

[0040] Use a linear function to fit the sample data taken from the calibration sample group with known concentrations in the principal component sample group to obtain the fitting curve.

[0041] The present invention also provides a quantitative detection device applying the high-accuracy immunochromatographic concentration detection method as described above, including a detection chamber, a sample tray disposed in the detection chamber, a laser generator, a filter system, an image acquisition device, and a thermal imaging system disposed in the detection chamber and above the sample tray, and a control processor respectively connected to the laser generator, the filter system, the image acquisition device, and the thermal imaging system.

[0042] It should be noted that by setting the fitting algorithm of the above multi-signal fusion immunochromatographic analysis method in the control processor device, the analysis of the three types of collected data and the result output can be automatically completed, avoiding the professional knowledge and cumbersome steps required for traditional manual drawing and regression fitting.

[0043] Furthermore, it also includes a rotating motor with an output end connected to the sample tray, and the rotating motor is connected to the control processor; a plurality of test strip sample slots are evenly distributed in a divergent manner along the circumference of the sample tray.

[0044] Furthermore, the laser generator is a laser generator with adjustable wavelength; specifically, an 808nm semiconductor linear array laser can be used to perform spatial selective preheating on the test sample test strip, and targeted thermal excitation is achieved by optimizing the laser power density (X W / cm 2 ).) and irradiation time (Y s).

[0045] Furthermore, the image acquisition device is an industrial camera; a high-sensitivity CMOS industrial camera is used for image acquisition.

[0046] Furthermore, the filter system is a filter, and the filter is provided on the lens of the image acquisition device;

[0047] Furthermore, the detection chamber includes a dark box with one end open, and a closed door detachably connected to the opening of the dark box, and the sample tray is correspondingly arranged at the opening position of the dark box. The detection chamber body adopts a fully enclosed dark box structure to isolate external light source interference, improve the stability of visible light and fluorescence signals. The closed dark box structure is combined with infrared response, and the infrared thermal imaging response is not affected by environmental temperature fluctuations, enabling the device to still output stable and consistent detection results in complex sample matrices or on-site environments, and having high anti-interference and repeatability.

[0048] The present invention also provides an operation procedure for the quantitative detection device as described above, including the following steps:

[0049] Place the test sample on the sample tray;

[0050] The control processor controls the laser generator to emit a visible light source to irradiate the test sample, and the image acquisition device captures the color-developed strip of the test strip to complete the collection of colorimetric signals; the control processor controls the laser generator to emit a fluorescence wavelength source to irradiate the test sample, and the image acquisition device filters and then collects the fluorescence labeling reaction intensity of the test sample; the control processor controls the laser generator to emit an infrared light source to irradiate the test sample, and the thermal imaging system collects the photothermal response for pseudo-color imaging and outputs the thermal signal of the test sample.

[0051] The control processor executes a preset data processing program to obtain concentration data output;

[0052] Take out the sample to be tested and complete a full-automatic immunochromatographic quantitative detection.

[0053] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0054] (1) By processing the data of the sample to be tested and the calibration sample group, the present invention establishes a combined sample group, obtains the principal component sample group by analyzing the principal components in the combined sample group using the principal component analysis method, establishes a data fitting curve of the principal component sample group, and calculates the concentration of the sample group to be tested with an unknown concentration based on the fitting curve. The calculated concentration value is more accurate and effective.

[0055] (2) By covering three signals for analysis and recognition, the present invention combines three analytical detection modes of visible light, fluorescence, and photothermal signals to comprehensively achieve quantitative analysis. In addition to the basic visible light determination, the double spectral overlap of the fluorescence signal improves the sensitivity of the fluorescence signal detection. The photothermal response provides a stable infrared signal output. The data are mutually compared and verified with each other. At the same time, there is also an infrared photothermal signal as a third comparison means, further increasing the comparison samples, and significantly improving the accuracy of quantitative detection.

[0056] (3) The present invention sets three signal recognitions and uses the principal component analysis method to establish a fitting curve, making the recognition of the sample to be tested more sensitive, especially having an advantage in the quantitative analysis of the sample to be tested with a low concentration. In the quantitative analysis of the sample to be tested with a normal concentration, due to multi-modal detection and data fitting processing, the experimental results are more reliable and accurate, and it is particularly suitable for scenarios where the actual sample concentration distribution is wide and the response is uneven. Description of the Drawings

[0057] Figure 1 It is a schematic flow chart of a high-accuracy immunochromatographic concentration detection method in an embodiment;

[0058] Figure 2 It is a perspective view of a quantitative detection device in an embodiment;

[0059] Figure 3 It is an exploded view of a quantitative detection device in an embodiment;

[0060] Figure 4 It is a schematic structural diagram of a sample tray in an embodiment.

[0061] 1 - Detection chamber, 11 - Dark box, 12 - Sealing door, 2 - Sample tray, 21 - Sample slot, 3 - Laser generator, 4 - Filter system, 5 - Image acquisition device, 6 - Thermal imaging system, 7 - Control processor, 8 - Rotating motor. Detailed Embodiments

[0062] The present invention will be further described below in conjunction with specific embodiments. Among them, the attached drawings are only for illustrative purposes, showing only schematic diagrams rather than physical diagrams, and should not be construed as a limitation of this patent; in order to better illustrate the embodiments of the present invention, some components in the attached drawings will be omitted, enlarged or reduced, which do not represent the dimensions of the actual product; for those skilled in the art, it is understandable that some well-known structures and their descriptions in the attached drawings may be omitted.

[0063] In order to make the objectives, technical solutions and advantages of the present application more clear, the present application will be further described in detail below in conjunction with the attached drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0064] In the attached drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components; in the description of the present invention, it should be understood that if there are terms such as "upper", "lower", "left", "right", etc. indicating the orientation or positional relationship, they are based on the orientation or positional relationship shown in the attached drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, the terms describing the positional relationship in the attached drawings are only for illustrative purposes and should not be construed as a limitation of this patent. For those of ordinary skill in the art, the specific meanings of the above terms can be understood according to specific circumstances.

[0065] Embodiment 1

[0066] As Figure 1 shown in the first embodiment of the present invention, a high-accuracy immunochromatographic concentration detection method specifically includes the following steps:

[0067] Combine a calibration sample group with known concentrations and a test sample group with unknown concentrations into a combined sample group;

[0068] Irradiate the combined sample group with visible light, capture the color development strip to collect the colorimetric signal of the calibration sample group, and obtain the visible light detection result;

[0069] Irradiate the combined sample group with an excitation light source of a specific wavelength, filter the light and collect the fluorescence labeling reaction intensity to obtain the fluorescence detection result;

[0070] Heat the combined sample group with a laser, perform false color imaging on the photothermal response in the combined sample group, and collect the thermal signal output to obtain the infrared detection result;

[0071] Standardize the visible light detection result, fluorescence detection result and infrared detection result of the combined sample group to obtain a standardized combined sample group;

[0072] Calculate the covariance matrix for the standardized combined sample group to obtain the principal component sample group;

[0073] Fit the sample data of the calibration sample group with known concentrations in the main component sample group to obtain a fitting curve;

[0074] Substitute the sample data of the test sample group with unknown concentrations in the main component sample group into the fitting curve to obtain the comprehensive concentration of the test sample group.

[0075] In this embodiment, the method for obtaining the visible light detection result is as follows:

[0076] Irradiate the test sample with visible light, collect the image information of the color development strip of the test sample through an industrial camera to obtain a colorimetric signal, convert the RGB image of the colorimetric signal to the CIE Lab uniform color space through color space conversion, and construct a color difference gray distribution matrix;

[0077] Specifically, taking the standard black (L* = 0, a* = 0, b* = 0) as the reference color, calculate the color difference value △E00 between each pixel point in the detection area and the reference color based on the color difference formula △E = [(△L*)^2 + (△a*)^2 + (△b*)^2] pixel by pixel, and construct a color difference gray distribution matrix, where the color difference value has a positive correlation with the gray value.

[0078] Perform projection integration on the color difference gray matrix in the horizontal direction to obtain the horizontal cumulative color difference distribution curve of the test sample;

[0079] According to the optical property differences between the sample reaction area and the substrate material, detect the local minimum points of the cumulative color difference distribution curve to achieve precise positioning and quantitative analysis of the test line and the control line, and obtain the visible light detection result.

[0080] Since there are optical property differences between the test line and the control line T / C line in the test paper reaction area and the substrate material, that is, the normal substrate area has a large cumulative color difference due to its high reflection property, while the immune reaction line area has a significant reduction in cumulative color difference due to the light absorption enhancement effect caused by the aggregation of nanomaterials. In this application, precise positioning and quantitative analysis of the test line and the control line are achieved by detecting the local minimum points of the cumulative color difference curve, effectively improving the objectivity and repeatability of the test strip detection of the test sample, and providing a reliable image processing solution for point-of-care testing devices.

[0081] In this embodiment, the method for obtaining the fluorescence detection result is as follows:

[0082] Irradiate the test sample with an excitation light source of a specific wavelength, filter out short-wavelength stray light with a filter, and collect the fluorescence labeling reaction intensity through an industrial camera to obtain the fluorescence distribution image of the test sample;

[0083] Specifically, a UV light source with a wavelength band of 365 - 370 nm is used. Through a 450 nm long - pass filter, short - wavelength stray light is effectively filtered out, and the fluorescence emission signal with a wavelength greater than 450 nm is retained. For image acquisition, an industrial camera can be used in combination with an optical imaging component to obtain the fluorescence distribution image of the test strip of the sample to be measured.

[0084] The fluorescence distribution image is converted to the RGB color space. Based on the spectral response characteristics of the fluorescence signal in the long - wavelength region, the R - channel data is preferentially extracted to generate a gray - scale distribution matrix. The gray - scale distribution matrix is projected and integrated along the horizontal direction to construct the axial fluorescence intensity distribution curve of the sample. An extreme - value detection algorithm is used to accurately locate the characteristic peak positions of the test line and the control line in the sample reaction area, and quantitative analysis is carried out to obtain the fluorescence detection result.

[0085] This application significantly improves the signal - to - noise ratio and positioning accuracy of weak fluorescence signals through a strategy combining spectral filtering and spatial integration.

[0086] In this embodiment, the method for obtaining the infrared detection result is as follows:

[0087] A laser is used to perform spatially selective pre - heating on the sample to be measured and achieve targeted thermal excitation. After thermal equilibrium, thermal imaging technology is used to collect the panoramic thermal distribution data of the color - developing area of the sample to be measured, and a two - dimensional temperature field matrix is obtained.

[0088] Multi - scale extreme - value search is implemented within the color - developing characteristic area, and a dynamic threshold segmentation method is used to delimit the effective detection area.

[0089] The extreme - value points of the temperature field are located by the gradient tracking method to obtain the infrared detection result.

[0090] Specifically, five groups of calibration samples with known concentrations and one group of samples to be measured with unknown concentrations are set. The combined sample group is formed by the above - mentioned method, and the visible - light detection result, fluorescence detection result, and infrared detection result of the combined sample group are calculated and obtained respectively:

[0091] Table 1 Detection results of the combined sample group

[0092]

[0093] In this embodiment, the method for obtaining the standardized combined sample group is as follows:

[0094] The mean and standard deviation of the visible - light detection result, fluorescence detection result, and infrared detection result in the combined sample group are calculated respectively;

[0095] According to the mean and standard deviation, the visible - light detection result, fluorescence detection result, and infrared detection result of the combined sample group are standardized:

[0096] z=(C - u) / v,

[0097] Where z is the standardized concentration of the sample to be measured, C is the directly measured value of the combined sample group, u is the mean value calculated for the combined sample group, and v is the standard deviation calculated for the combined sample group.

[0098] It should be noted that C is the directly measured value of the combined sample group. For visible light detection and fluorescence detection, the directly measured value C is the integral of gray-scale pixel values or the ratio of the gray-scale pixel integrals of the test line and the control line; for photothermal detection, C is the temperature value.

[0099] Specifically, according to the above method, the visible light detection results, fluorescence detection results, and infrared detection results of the combined sample group are standardized to obtain the standardized combined data:

[0100] Table 2 Standardized combined sample group data

[0101]

[0102] In this embodiment, the method for obtaining the principal component sample group is as follows:

[0103] Take the eigenvector corresponding to the largest eigenvalue of the covariance matrix, and perform a cross product of the eigenvector with the measured values of the visible light detection results, fluorescence detection results, and infrared detection results in the standardized sample group, which is denoted as the principal component sample data;

[0104] Perform a cross product of each group of measured values in the standardized combined sample group with the eigenvector, and form all the obtained principal component sample data into a principal component sample group.

[0105] Specifically, in this embodiment, after obtaining the covariance matrix of the data of the above standardized combined sample group, find the eigenvector a = [0.57757515, 0.57846955, 0.5760034] corresponding to the largest eigenvalue, and perform a cross product of the eigenvector with the measured values of each group of data to obtain the principal component values of the standardized combined sample group, and establish the principal component sample data:

[0106] Table 3 Principal component sample group data

[0107]

[0108] In this embodiment, the method for establishing the fitting curve is as follows:

[0109] Use a linear function to fit the sample data taken from the calibration sample group with known concentrations in the principal component sample group to obtain the fitting curve.

[0110] Specifically, the first 5 groups of data in the principal component sample group are fitted into a standard curve using the least squares method, f(x) = 27.020853x + 15.999999, to obtain the fitting curve.

[0111] In this embodiment, to calculate the concentration of a sample to be measured with an unknown concentration, the principal component value of the 6th sample to be measured in the principal component sample group is substituted into the fitting curve, and the unknown concentration of the sample to be measured is obtained as 101.9920714 ug / kg.

[0112] The above data fusion processing scheme can improve the accuracy of the finally output concentration data, automatically complete data analysis and result output, avoid the professional knowledge and cumbersome steps required for traditional manual drawing and regression fitting. Cross-validation can be carried out between various collected data modalities to improve the detection reliability, and stable and consistent detection results can still be output in complex sample matrices or on-site environments.

[0113] The advantages of this embodiment are as follows: The present invention processes the data of the sample to be measured and the calibration sample group to establish a combined sample group. By analyzing the principal components within the combined sample group and using the principal component analysis method, a principal component sample group is obtained, and a data fitting curve of the principal component sample group is established. Based on the fitting curve, the concentration of the sample group to be measured with an unknown concentration is calculated, and the calculated concentration value is more accurate and effective. The present invention analyzes and identifies by covering three signals, combines three analysis and detection modes of visible light, fluorescence, and photothermal signals to comprehensively achieve quantitative analysis. In addition to the basic visible light determination, the double spectral overlap of the fluorescence signal improves the sensitivity of fluorescence signal detection, and the photothermal response provides a stable infrared signal output. The data are mutually compared and demonstrated, and at the same time, the infrared photothermal signal is used as a third comparison means to further increase the comparison samples, significantly improving the accuracy of quantitative detection. The present invention sets three signal identifications and uses the principal component analysis method to establish a fitting curve, making the identification of the sample to be measured more sensitive, especially having advantages in the quantitative analysis of samples to be measured with low concentrations. In the quantitative analysis of samples to be measured with normal concentrations, due to multi-modal detection and data fitting processing, the experimental results are more reliable and accurate, and it is particularly suitable for scenarios where the actual sample concentration distribution is wide and the response is uneven.

[0114] Embodiment 2

[0115] A quantitative detection device applying the high-accuracy immunochromatographic concentration detection method as described in the above Embodiment 1 in this embodiment:

[0116] As Figure 2 and Figure 3 shown, it includes a detection chamber 1, a sample tray 2 arranged in the detection chamber 1, a laser generator 3, a filter system 4, an image acquisition device 5, and a thermal imaging system 6 arranged in the detection chamber 1 and above the sample tray 2, and a control processor 7 respectively connected to the laser generator 3, the filter system 4, the image acquisition device 5, and the thermal imaging system 6.

[0117] It should be noted that by setting the fitting algorithm of the above multi-signal fusion immunochromatographic analysis method in the control processor 7 device, the analysis and result output of the three types of collected data can be automatically completed, avoiding the professional knowledge and cumbersome steps required for traditional manual drawing and regression fitting.

[0118] In this embodiment, test paper sample slots 21 are distributed on the sample tray 2.

[0119] In this embodiment, the laser generator 3 is a laser generator with adjustable wavelength; specifically, an 808nm semiconductor linear array laser can be used to perform spatial selective preheating on the test sample test strip, and the target thermal excitation is realized by optimizing the laser power density X W / cm 2 and the irradiation time Y s.

[0120] In this embodiment, the image acquisition device 5 is an industrial camera; a high-sensitivity CMOS industrial camera is used for image acquisition.

[0121] In this embodiment, the filter system 4 is a filter, and the filter is arranged on the lens of the image acquisition device 5;

[0122] In this embodiment, the thermal imaging system 6 can adopt a DIY-Thermocam V3 thermal imaging system 6 based on a LEPTON3.5 long-wave infrared detection module, with a working band of 8-14μm for infrared thermal radiation detection. The thermal detector of this thermal imaging system 6 has a spatial resolution of 160×120 pixels, can detect a temperature range of -10°C to +450°C, and the temperature sensitivity reaches 50mKΔT < 0.05°C.

[0123] As Figure 3 shown, the detection chamber 1 includes a light-tight box 11 with one end open, and a closing door 12 detachably connected to the opening of the light-tight box 11. The sample tray 2 is correspondingly arranged at the opening position of the light-tight box 11.

[0124] The detection chamber 1 body adopts a fully enclosed light-tight box 11 structure to isolate external light source interference and improve the stability of visible light and fluorescence signals. The enclosed light-tight box 11 structure combines infrared response, and the infrared thermal imaging response is not affected by environmental temperature fluctuations, enabling the device to still output stable and consistent detection results in complex sample matrices or on-site environments, with high anti-interference and repeatability.

[0125] The operation steps of this embodiment specifically include the following steps:

[0126] Place the test sample on the sample tray 2;

[0127] The control processor 7 controls the laser generator 3 to emit a visible light source to irradiate the sample to be tested, and the image acquisition device 5 captures the colorimetric strip of the test strip to complete the collection of colorimetric signals; the control processor 7 controls the laser generator 3 to emit a fluorescence wavelength light source to irradiate the sample to be tested, and the image acquisition device 5 filters and collects the fluorescence labeling reaction intensity of the sample to be tested; the control processor 7 controls the laser generator 3 to emit an infrared light source to irradiate the sample to be tested, and the thermal imaging system 6 collects the photothermal response for pseudo-color imaging and outputs the thermal signal of the sample to be tested;

[0128] The control processor 7 executes a preset data processing program to obtain and output concentration data;

[0129] Take out the sample to be tested to complete a full-automatic immunochromatographic quantitative detection.

[0130] Embodiment 3

[0131] This embodiment is similar to Embodiment 2, the difference lies in that in this embodiment:

[0132] As Figure 2 and Figure 3 shown, it further includes a rotation motor 8 whose output end is connected to the sample tray 2, and the rotation motor 8 is connected to the control processor 7;

[0133] As Figure 4 shown, 24 test strip sample slots 21 are evenly distributed in a circumferentially divergent manner on the sample tray 2.

[0134] The control processor 7 controls the rotation motor 8 to drive the sample tray 2 to rotate, which can move the sample tray 2 under the corresponding collection device during different data collections, or switch to the next sample for collection after completing the collection of one sample, realizing automatic collection and automatic switching, greatly improving the collection efficiency and the detection rate.

[0135] Obviously, the above-mentioned embodiments of the present invention are merely examples for clearly illustrating the present invention, rather than limiting the implementation manners of the present invention. For those of ordinary skill in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to enumerate all the implementation manners here. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the claims of the present invention.

Claims

1. A high-accuracy immunochromatographic concentration detection method, characterized in that, Specifically, it includes the following steps: Combine the calibration sample group with known concentration and the test sample group with unknown concentration into a combined sample group; Irradiate the combined sample group with visible light, capture the color development strip to collect the colorimetric signal of the calibration sample group, and obtain the visible light detection result; Irradiate the combined sample group with an excitation light source of a specific wavelength, filter the light, and collect the fluorescence labeling reaction intensity to obtain the fluorescence detection result; Use laser to heat the combined sample group, perform false color imaging on the photothermal response in the combined sample group, collect the thermal signal output, and obtain the infrared detection result; Standardize the visible light detection result, fluorescence detection result, and infrared detection result of the combined sample group to obtain a standardized combined sample group; Calculate the covariance matrix for the standardized combined sample group to obtain the principal component sample group; Fit the sample data taken from the calibration sample group with known concentration in the principal component sample group to obtain a fitting curve; Substitute the sample data taken from the test sample group with unknown concentration in the principal component sample group into the fitting curve to obtain the comprehensive concentration of the test sample group.

2. The highly accurate immunochromatographic concentration detection method according to claim 1, wherein The method for obtaining the visible light detection result is as follows: Irradiate the sample with visible light, collect the image information of the sample color development strip through an industrial camera to obtain the colorimetric signal, convert the RGB image of the colorimetric signal to the CIE Lab uniform color space through color space conversion, and construct a color difference gray distribution matrix; Perform projection integration on the color difference gray matrix in the horizontal direction to obtain the horizontal cumulative color difference distribution curve of the sample; According to the optical property differences between the sample reaction area and the substrate material, detect the local minimum points of the cumulative color difference distribution curve, realize the precise positioning and quantitative analysis of the detection line and the control line, and obtain the visible light detection result.

3. A highly accurate immunochromatographic concentration detection method according to claim 1, characterized in that, The method for obtaining the fluorescence detection result is as follows: Irradiate the sample with an excitation light source of a specific wavelength, use a filter to filter out short-wavelength stray light, collect the fluorescence labeling reaction intensity through an industrial camera, and obtain the fluorescence distribution image of the sample; Convert the fluorescence distribution image to the RGB color space, based on the spectral response characteristics of the fluorescence signal in the long-wavelength region, preferentially extract the R-channel data to generate a gray distribution matrix, perform projection integration on the gray distribution matrix in the horizontal direction, construct the axial fluorescence intensity distribution curve of the sample, use the extreme value detection algorithm to precisely locate the characteristic peak positions of the detection line and the control line in the sample reaction area, and perform quantitative analysis to obtain the fluorescence detection result.

4. A highly accurate immunochromatographic concentration detection method according to claim 1, characterized in that The method for obtaining the infrared detection result is as follows: Use laser to perform spatially selective preheating on the sample and achieve targeted thermal excitation. After thermal equilibrium, use thermal imaging technology to collect the panoramic thermal distribution data of the sample color development area to obtain a two-dimensional temperature field matrix; Implement multi-scale extreme value search within the color development characteristic area, and use the dynamic threshold segmentation method to delimit the effective detection area; Locate the extreme value points of the temperature field through the gradient tracking method to obtain the infrared detection result.

5. A highly accurate immunochromatographic concentration detection method according to claim 1, characterized in that The method for obtaining the standardized combined sample group is as follows: Calculate the mean and standard deviation of the visible light detection result, fluorescence detection result, and infrared detection result in the combined sample group respectively; According to the mean and standard deviation, standardize the visible light detection result, fluorescence detection result, and infrared detection result of the combined sample group: z = (C - u) / v Where z is the standardized concentration of the sample to be measured, C is the directly measured value of the combined sample group, u is the mean value calculated for the combined sample group, and v is the standard deviation calculated for the combined sample group.

6. The highly accurate immunochromatographic concentration detection method according to claim 1, wherein The method for obtaining the principal component sample group is as follows: Take the eigenvector corresponding to the largest eigenvalue of the covariance matrix, and perform a cross product of the eigenvector with the measured values of the visible light detection result, fluorescence detection result, and infrared detection result in the standardized sample group, which is denoted as the principal component sample data; Perform a cross product of each set of measured values in the standardized combined sample group with the eigenvector, and form the principal component sample data obtained into the principal component sample group.

7. A highly accurate immunochromatographic concentration detection method according to claim 1, characterized in that, The method for establishing the fitting curve is as follows: Use a linear function to fit the sample data from the calibration sample group with known concentrations in the principal component sample group to obtain the fitting curve.

8. A detection device applying the high-accuracy immunochromatographic concentration detection method according to any one of claims 1-7, characterized in that, It includes a detection chamber (1), a sample tray (2) provided in the detection chamber (1), a laser generator (3), a filter system (4), an image acquisition device (5), and a thermal imaging system (6) provided in the detection chamber (1) and above the sample tray (2), and a control processor (7) respectively connected to the laser generator (3), the filter system (4), the image acquisition device (5), and the thermal imaging system (6).

9. The detection device according to claim 8, wherein, It further includes a rotation motor (8) with an output end connected to the sample tray (2), and the rotation motor (8) is connected to the control processor (7); a plurality of test paper sample slots (21) are evenly distributed in a circumferentially divergent manner on the sample tray (2).

10. The detection device according to claim 8, characterized in that, The laser generator (3) is a laser generator with adjustable wavelength, the image acquisition device (5) is an industrial camera, the filter system (4) is a filter, and the filter is provided on the lens of the image acquisition device (5); The detection chamber (1) includes a light-tight box (11) with one end open, and a closing door (12) detachably connected to the opening of the light-tight box (11), and the sample tray (2) is correspondingly arranged at the opening position of the light-tight box (11).

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