Automated Line Detection on Lateral Flow Assays: A Paradigm Shift in Rapid Diagnostic Testing

Lateral flow assays (LFAs) provide rapid, accurate, and affordable results for disease diagnostics in resource-limited and point-of-care settings. However, the manual interpretation of LFA results can introduce human errors and biases. In this paper, we detail an automated line detection system that can read and interpret LFA results based on the image taken using a smartphone or any other digital imaging device. The proposed system can self identify the test and control lines of the LFA and can be used to quantify the analyte post calibration The automated line detection system reduces the reliance on trained personnel and enhances the accuracy and reliability of LFA readouts. This work details the various steps from image acquisition to detection of the test and control lines of a sensitive LFA and also evaluated an increase in sensitivity of detection due to the readout automation. In conclusion, the automated line detection can generate more accurate and consistent data than manual interpretation, which can be used to make better decisions for patient care.