A Handheld Reader with Optimized Image Analysis for HIV Lateral Flow Test

Dong, Xiaobin; Zhu, Rui; Yang, Wenbo; Zhang, Lulu; Qiu, Xianbo; Dong, Shenghua; Zhang, Xiaolei; Ge, Shengxiang; Xia, Ningshao

doi:10.1109/cisp-bmei60920.2023.10373323

Cited by 1 publication

(1 citation statement)

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“…Various Image processing algorithms for the analysis of lateral flow assay images have been developed and reported in the literature [11][12][13][14][15][16][17][18][19][20][21] ,most of which pertain to the development of smartphone applications for the accurate interpretation of the test results by the end-user. However, while the LFAs are being designed in the laboratory, the researchers need to 'run the standards,' i.e., perform the assay at several different analyte concentrations, in many replicates for each concentration to generate a standard calibration (signal-response) curve for the proposed assay.…”

Section: Introductionmentioning

confidence: 99%

Streamlining Lateral Flow Assay (LFA) Data Analysis: A MATLAB® Live Script for Integrated Batch Image Processing and Limit of Detection Determination

Saxena,

Toley

2024

Preprint

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Lateral flow assays (LFAs) are widely utilized for rapid point-of-care diagnostics in various fields; however, their quantitative image analysis is frequently hindered by repetitive manual processes and inconsistencies, typically involving the use of combinations of image processing and data analysis software tools. This protocol introduces a MATLAB live-script-based code for the integrated batch processing of LFA images and standard curve development. This code simplifies quantitative LFA analysis by automating image processing, peak detection, statistical analysis, and data fitting to a 4-parameter logistic curve for accurate Limit of Detection (LoD) determination. This approach significantly minimizes manual intervention and the potential for human error, thereby enhancing reproducibility. This addresses the critical need for efficient and reliable LFA data analysis in research laboratories. By offering a standardized method for LFA image processing and data analysis, this protocol facilitates faster and more consistent research outcomes.

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