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

IF 2.9 3区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES PLoS ONE Pub Date : 2024-10-04 eCollection Date: 2024-01-01 DOI:10.1371/journal.pone.0311343
Nidhi Menon, David Beery, Prava Sharma, Adrian Crutchfield, Leah Kim, Aaron Lauer, Ayesha Azimuddin, Brianna Wronko-Stevens
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Abstract

Color correction is an important methodology where a digital image's colors undergo a transformation to more accurately represent their appearance using a predefined set of illumination conditions. Colorimetric measurements in diagnostics are sensitive to very small changes in colors and therefore require consistent, reproducible illumination conditions to produce accurate results, making color correction a necessity. This paper presents an image color correction pipeline developed by HueDx, Inc., using transfer algorithms that improve upon existing methodologies and demonstrates real-world applications of this pipeline in colorimetric clinical chemistry using a smartphone enabled, paper-based total protein diagnostic assay. Our pipeline is able to compensate for a variety of illumination conditions to provide consistent imaging for quantitative colorimetric measurements using white-balancing, multivariate gaussian distributions and histogram regression via dynamic, non-linear interpolating lookup tables. We empirically demonstrate that each point in the color correction pipeline provides a theoretical basis for achieving consistent and precise color correction. To show this, we measure color difference with deltaE (ΔE00), alongside quantifying performance of the HueDx color correction system, including the phone hardware, color sticker manufacturing quality and software correction capabilities. The results show that the HueDx color correction system is capable of restoring images to near-imperceptible levels of difference independent of their original illumination conditions including brightness and color temperature. Comparisons drawn from the paper-based total protein assay calibrated and quantified with and without using the HueDx color correction pipeline show that the coefficient of variation in precision testing is almost twice as high without color-correcting. Limits of blank, detection and quantitation were also higher without color-correction. Overall, we were able to demonstrate the HueDx platform improves reading and outcome of the total protein diagnostic assay and is useful for the development of smartphone-based quantitative colorimetric diagnostic assays for point-of-care testing.

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利用 HueDx 色彩校正系统,开发一种支持智能手机的纸质定量诊断测定。
色彩校正是一种重要的方法,在这种方法中,数字图像的色彩经过转换,以便在一组预定义的照明条件下更准确地呈现其外观。诊断中的色度测量对颜色的微小变化非常敏感,因此需要一致、可重现的照明条件才能产生准确的结果,这就使得色彩校正成为必要。本文介绍了由 HueDx 公司开发的图像色彩校正管道,该管道采用了对现有方法进行改进的转移算法,并使用支持智能手机的纸质总蛋白诊断分析仪演示了该管道在比色临床化学中的实际应用。我们的管道能够补偿各种照明条件,通过动态非线性插值查找表,利用白平衡、多元高斯分布和直方图回归,为定量比色测量提供一致的成像。我们通过经验证明,色彩校正管道中的每一点都为实现一致、精确的色彩校正提供了理论基础。为了证明这一点,我们用 deltaE(ΔE00)测量色差,同时量化 HueDx 色彩校正系统的性能,包括手机硬件、彩色贴纸的制造质量和软件校正能力。结果表明,HueDx 色彩校正系统能够将图像还原到接近可感知的差异水平,而不受亮度和色温等原始照明条件的影响。对使用和未使用 HueDx 色彩校正管道进行校准和定量的纸基总蛋白检测进行的比较显示,未使用色彩校正时,精确度测试的变异系数几乎是使用 HueDx 色彩校正时的两倍。未经颜色校正的空白、检测和定量界限也更高。总之,我们能够证明 HueDx 平台提高了总蛋白诊断测定的读数和结果,并有助于开发基于智能手机的定量比色诊断测定,用于护理点检测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
PLoS ONE
PLoS ONE 生物-生物学
CiteScore
6.20
自引率
5.40%
发文量
14242
审稿时长
3.7 months
期刊介绍: PLOS ONE is an international, peer-reviewed, open-access, online publication. PLOS ONE welcomes reports on primary research from any scientific discipline. It provides: * Open-access—freely accessible online, authors retain copyright * Fast publication times * Peer review by expert, practicing researchers * Post-publication tools to indicate quality and impact * Community-based dialogue on articles * Worldwide media coverage
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