A Quantitative Detection Algorithm for Multi-Test Line Lateral Flow Immunoassay Applied in Smartphones

The traditional lateral flow immunoassay (LFIA) detection method suffers from issues such as unstable results and low quantitative accuracy. In this study, we propose a novel multi-test line using smartphone-based SAA strips. Following the utilization of image processing techniques to extract analyze pigments on strips, analysis was conducted. Experimental setups with controlled lighting conditions in dark box were designed capture samples smartphones different specifications for analysis. algorithm’s sensitivity robustness validated by introducing noise samples, performance strips algorithms determined. experimental demonstrate that proposed based achieves an accuracy rate 94.23% 260 which is comparable methods but higher stability lower algorithm complexity.