When seeing is not believing: application-appropriate validation matters for quantitative bioimage analysis
Author:
Publisher
Springer Science and Business Media LLC
Subject
Cell Biology,Molecular Biology,Biochemistry,Biotechnology
Link
https://www.nature.com/articles/s41592-023-01881-4.pdf
Reference18 articles.
1. Chen, J. et al. Preprint at bioRxiv https://doi.org/10.1101/491035 (2018).
2. Viana, M. P. et al. Nature 613, 345–354 (2023).
3. Guan, H. & Liu, M. IEEE Trans. Biomed. Eng. 69, 1173–1185 (2022).
4. Yang, J., Zhou, K., Li, Y. & Liu, Z. Preprint at arXiv https://doi.org/10.48550/arXiv.2110.11334 (2021).
5. Fernando, T., Gammulle, H., Denman, S., Sridharan, S. & Fookes, C. ACM Comput. Surv. 54, 1–37 (2022).
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Believing is seeing – the deceptive influence of bias in quantitative microscopy;Journal of Cell Science;2024-01-01
2. MMV_Im2Im: an open-source microscopy machine vision toolbox for image-to-image transformation;GigaScience;2024
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