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Review
. 2024 Jul;295(1):61-82.
doi: 10.1111/jmi.13208. Epub 2023 Jun 9.

Made to measure: An introduction to quantifying microscopy data in the life sciences

Siân Culley  1 , Alicia Cuber Caballero  1 , Jemima J Burden  2 , Virginie Uhlmann  3
Affiliations
Review

Made to measure: An introduction to quantifying microscopy data in the life sciences

Siân Culley et al. J Microsc. 2024 Jul.

Abstract

Images are at the core of most modern biological experiments and are used as a major source of quantitative information. Numerous algorithms are available to process images and make them more amenable to be measured. Yet the nature of the quantitative output that is useful for a given biological experiment is uniquely dependent upon the question being investigated. Here, we discuss the 3 main types of information that can be extracted from microscopy data: intensity, morphology, and object counts or categorical labels. For each, we describe where they come from, how they can be measured, and what may affect the relevance of these measurements in downstream data analysis. Acknowledging that what makes a measurement 'good' is ultimately down to the biological question being investigated, this review aims at providing readers with a toolkit to challenge how they quantify their own data and be critical of conclusions drawn from quantitative bioimage analysis experiments.

Keywords: bioimage analysis; bioimaging; microscopy; quantification.

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References

REFERENCES

    1. Myers, G. (2012). Why bioimage informatics matters. Nature Methods, 9, 659–660. https://doi.org/10.1038/nmeth.2024
    1. Meijering, E., Carpenter, A. E., Peng, H., Hamprecht, F. A., & Olivo‐Marin, J.‐C. (2016). Imagining the future of bioimage analysis. Nature Biotechnology, 34, 1250–1255. https://doi.org/10.1038/nbt.3722
    1. Murphy, R. F. (2014). A new era in bioimage informatics. Bioinformatics, 30, 1353–1353. https://doi.org/10.1093/bioinformatics/btu158
    1. Jamali, N., Dobson, E. T. A., Eliceiri, K. W., Carpenter, A. E., & Cimini, B. A. (2022). 2020 BioImage Analysis Survey: Community experiences and needs for the future. Biological Imaging, 1, e4. https://doi.org/10.1017/S2633903x21000039
    1. Eliceiri, K. W., Berthold, M. R., Goldberg, I. G., Ibáñez, L., Manjunath, B. S., Martone, M. E., Murphy, R. F., Peng, H., Plant, A. L., Roysam, B., Stuurman, N., Swedlow, J. R., Tomancak, P., & Carpenter, A. E. (2012). Biological imaging software tools. Nature Methods, 9, 697–710. https://doi.org/10.1038/nmeth.2084

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