Development of a smartphone enabled, paper-based quantitative diagnostic assay using the HueDx color correction...

Area of Science:

• Digital imaging
• Color science
• Clinical diagnostics

Background:

• Colorimetric measurements are crucial for diagnostics but sensitive to illumination.
• Consistent and reproducible lighting is essential for accurate colorimetric results.
• Existing color correction methods have limitations in real-world applications.

Purpose of the Study:

• To present an advanced image color correction pipeline for quantitative colorimetric measurements.
• To demonstrate the pipeline's effectiveness in smartphone-based diagnostic assays.
• To improve accuracy and reproducibility in point-of-care testing.

Main Methods:

• Developed a HueDx color correction pipeline using transfer algorithms.
• Employed white-balancing, multivariate Gaussian distributions, and histogram regression.
• Utilized dynamic, non-linear interpolating lookup tables for compensation.
• Quantified performance using deltaE (ΔE00) and precision testing.

Main Results:

• The HueDx system restores images to near-imperceptible color differences across various lighting.
• Color correction significantly reduces the coefficient of variation in precision testing.
• Improved limits of blank, detection, and quantitation were observed with the pipeline.

Conclusions:

• The HueDx color correction platform enhances the accuracy and outcomes of diagnostic assays.
• The pipeline is effective in compensating for diverse illumination conditions.
• The system is valuable for developing smartphone-based quantitative colorimetric diagnostic assays for point-of-care use.