Digital postprocessing and image segmentation for objective analysis of colorimetric reactions

M. Shane Woolf, Leah M. Dignan, Anchi T. Scott, James P. Landers

Published: 2020-12-08 DOI: 10.1038/s41596-020-00413-0

colorimetric reactions

image segmentation

digital postprocessing

ImageJ

low-cost detection

AI 解读

暂无数据

Using high-resolution microscopy data to generate realistic structures for electromagnetic FDTD simulations from complex biological models

Experimental modulation of physiological force application on leg joint neurons in intactDrosophila melanogaster

Mitochondrial single-cell ATAC-seq for high-throughput multi-omic detection of mitochondrial genotypes and chromatin accessibility

Identification, isolation and analysis of human gut-associated lymphoid tissues

Development of RNA G-quadruplex (rG4)-targetingl-RNA aptamers by rG4-SELEX

Self-assembled ultraflexible probes for long-term neural recordings and neuromodulation

Hyperpolarized water as universal sensitivity booster in biomolecular NMR

Improved sampling and DNA extraction procedures for microbiome analysis in food-processing environments

An analytical workflow for dynamic characterization and quantification of metal-bearing nanomaterials in biological matrices

A flow cytometry-based protocol for syngenic isolation of neurovascular unit cells from mouse and human tissues

查看全部

Sections

Figures

References

Lee, B. B. The evolution of concepts of color vision. Neurociencias 4, 209–224 (2008).
Molday, R. S. & Moritz, O. L. Photoreceptors at a glance. J. Cell Sci. 128, 4039–4045 (2015).
Jameson, K. A. in The Oxford Companion to Consciousness 155–158 (Oxford University Press, 2009).
Krauss, S. T. et al. Objective method for presumptive field-testing of illicit drug possession using centrifugal microdevices and smartphone analysis. Anal. Chem. 88, 8689–8697 (2016).
CIE. Commission internationale de l’eclairage proceedings, 1931 (Cambridge University, 1932).
Smith, T. & Guild, J. The CIE colorimetric standards and their use. Trans. Opt. Soc. 33, 73 (1931).
CIE. Colorimetry-Part 4: CIE 1976 L* a* b* colour space. International Organization for Standardization https://www.iso.org/standard/74166.html (2008).
Schnapf, J., Kraft, T. & Baylor, D. Spectral sensitivity of human cone photoreceptors. Nature 325, 439–441 (1987).
Anderson, M., Motta, R., Chandrasekar, S. & Stokes, M. in Color and Imaging Conference 238–245 (Society for Imaging Science and Technology, 1996).
Schneider, C. A., Rasband, W. S. & Eliceiri, K. W. NIH Image to ImageJ: 25 years of image analysis. Nat. Methods 9, 671–675 (2012).
Rueden, C. T. et al. ImageJ2: ImageJ for the next generation of scientific image data. BMC Bioinformatics 18, 529 (2017).
Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676 (2012).
Roels, J. et al. An interactive ImageJ plugin for semi-automated image denoising in electron microscopy. Nat. Commun. 11, 1–13 (2020).
Boudaoud, A. et al. FibrilTool, an ImageJ plug-in to quantify fibrillar structures in raw microscopy images. Nat. Protoc. 9, 457 (2014).
Krauss, S. T., Holt, V. C. & Landers, J. P. Simple reagent storage in polyester-paper hybrid microdevices for colorimetric detection. Sens. Actuators B Chem. 246, 740–747 (2017).
Krauss, S. T., Nauman, A. Q., Garner, G. T. & Landers, J. P. Color manipulation through microchip tinting for colorimetric detection using hue image analysis. Lab Chip 17, 4089–4096 (2017).
Krauss, S. T. et al. Centrifugal microfluidic devices using low-volume reagent storage and inward fluid displacement for presumptive drug detection. Sens. Actuators B Chem. 284, 704–710 (2019).
Thompson, B. L., Wyckoff, S. L., Haverstick, D. M. & Landers, J. P. Simple, reagentless quantification of total bilirubin in blood via microfluidic phototreatment and image analysis. Anal. Chem. 89, 3228–3234 (2017).
Jackson, K. R. et al. A novel loop-mediated isothermal amplification method for identification of four body fluids with smartphone detection. Forensic Sci. Int. Genet. 45, 102195 (2020).
Russell, R. A. et al. Segmentation of fluorescence microscopy images for quantitative analysis of cell nuclear architecture. Biophys. J. 96, 3379–3389 (2009).
Balsam, J., Bruck, H. A., Kostov, Y. & Rasooly, A. Image stacking approach to increase sensitivity of fluorescence detection using a low cost complementary metal-oxide-semiconductor (CMOS) webcam. Sens. Actuators B Chem. 171, 141–147 (2012).
Perez, A. J. et al. A workflow for the automatic segmentation of organelles in electron microscopy image stacks. Front. Neuroanat. 8, 126 (2014).
Stegmaier, J. et al. Fast segmentation of stained nuclei in terabyte-scale, time resolved 3D microscopy image stacks. PLoS ONE 9, e90036 (2014).
Capitan-Vallvey, L. F., Lopez-Ruiz, N., Martinez-Olmos, A., Erenas, M. M. & Palma, A. J. Recent developments in computer vision-based analytical chemistry: a tutorial review. Anal. Chim. Acta 899, 23–56 (2015).
Cao, S., Huang, D., Wang, Y. & Li, G. in Advances in Mechanical and Electronic Engineering 381–386 (Springer, 2012).
Cantrell, K., Erenas, M., de Orbe-Payá, I. & Capitán-Vallvey, L. Use of the hue parameter of the hue, saturation, value color space as a quantitative analytical parameter for bitonal optical sensors. Anal. Chem. 82, 531–542 (2010).
Ibraheem, N. A., Hasan, M. M., Khan, R. Z. & Mishra, P. K. Understanding color models: a review. ARPN J. Sci. Technol. 2, 265–275 (2012).
Hanbury, A. The taming of the hue, saturation and brightness colour space. Proc. 7th Computer Vision Winter Workshop http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.3.2574 (2002).
Barthel, K. U. 3D-data representation with ImageJ. Proc. 1st ImageJ User & Developer Conference http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.414.725 (2006).
Clark, C. P. et al. Closable valves and channels for polymeric microfluidic devices. Micromachines 11, 627 (2020).
Tian, Z., Liu, L. Q., Peng, C., Chen, Z. & Xu, C. A new development of measurement of 19-Nortestosterone by combining immunochromatographic strip assay and ImageJ software. Food Agric. Immunol. 20, 1–10 (2009).
Hwang, J., Kwon, D., Lee, S. & Jeon, S. Detection of Salmonella bacteria in milk using gold-coated magnetic nanoparticle clusters and lateral flow filters. RSC Adv. 6, 48445–48448 (2016).
Kortli, S. et al. Yersinia pestis detection using biotinylated dNTPs for signal enhancement in lateral flow assays. Anal. Chim. Acta 1112, 54–61 (2020).
Adkins, J. A. et al. Colorimetric and electrochemical bacteria detection using printed paper-and transparency-based analytic devices. Anal. Chem. 89, 3613–3621 (2017).
Tanner, N. A., Zhang, Y. & Evans, T. C. Jr Visual detection of isothermal nucleic acid amplification using pH-sensitive dyes. Biotechniques 58, 59–68 (2015).
Zhang, Y. et al. Rapid molecular detection of SARS-CoV-2 (COVID-19) virus RNA using colorimetric LAMP. Preprint at https://www.medrxiv.org/content/10.1101/2020.02.26.20028373v1 (2020).
Singh, H. K., Tomar, S. K. & Maurya, P. K. Thresholding techniques applied for segmentation of RGB and multispectral images. https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.735.9363&rep=rep1&type=pdf (2012).

Digital postprocessing and image segmentation for objective analysis of colorimetric reactions

推荐阅读