Design And Algorithm Research Of Fluorescence Immunoassay Strip Imaging System

Fluorescence immunochromatography is an emerging substance concentration measurement technique that combines antigen-antibody-specific reaction with fluorescence analysis methods.The technology has the advantages of high precision,wide dynamic detection range,and high sensitivity.With the continuous development of research on this technology,the design and implementation of a set of fluorescent immunochromatography quantitative detection system will have broad application prospects in biochemical detection and medical diagnostics and other related fields.After analyzing the quantitative detection technology of fluorescent detection strips at home and abroad,this paper designs the fluorescent immunometric strip imaging system based on the principle of fluorescence immunoassay.The main research content of this article is as follows.The development and research status of fluorescence immunochromatographic assay technology are introduced.The basic principles of fluorescence quantitative analysis and immunochromatographic assay are described.The mathematical relationship between the fluorescence intensity and the analyte concentration is analyzed.The structural design of the fluorescence immunochromatographic strip imaging detection system was completed.The imaging system adopts a ring-shaped LED lamp as a light source to increase uniform and sufficient excitation light.The CMOS camera is used as an image sensor of the system,and a system filter is used to remove stray light according to the fluorescence spectrum characteristic of the test strip to be acquired by a hand-held zoom microscope.High-definition test strip image.According to the characteristics of fluorescence immunochromatography strips,an efficient algorithm for extracting fluorescence signals from strips was designed.The algorithms mainly include image channel separation,image preprocessing,image segmentation,image location,background filtering,and calculation of feature values.And fitting and other steps.The core image segmentation process uses two-dimensional maximum entropy genetic algorithm to extract the fluorescence region.Experiments show that the two-dimensional maximum entropy genetic algorithm has strong anti-noise ability and good segmentation effect,and can realize segmentation of low-concentration test strip images.The performance of the system was tested using standard concentration control strips and PGII fluorescent immunochromatographic test strips.The fit of the standard concentration control strips and the PGII fluorescence immunochromatographic strip test results fitted a resolution of 0.99944 and 0.99142,respectively.The test results show that the design system can basically achieve the desired effect and can achieve the detection of the test strip concentration.Finally,through experimental tests,it is proved that the system also has good repeatability and stability.