The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
CellProfiler 3.0: Next-generation image processing for biology
Open accessAbstract
CellProfiler has enabled the scientific research community to create flexible, modular image analysis pipelines since its release in 2005. Here, we describe CellProfiler 3.0, a new version of the software supporting both whole-volume and plane-wise analysis of three-dimensional (3D) image stacks, increasingly common in biomedical research. CellProfiler's infrastructure is greatly improved, and we provide a protocol for cloud-based, large-scale image processing. New plugins enable running pretrained deep learning models on images. Designed by and for biologists, CellProfiler equips researchers with powerful computational tools via a well-documented user interface, empowering biologists in all fields to create quantitative, reproducible image analysis workflows.
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Cites
ImageNet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155
U-Net: Convolutional Networks for Biomedical Image Segmentation
Ronneberger, O., Fischer, P., & Brox, T. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-24574-4_28 · Cited by 99,404
LeCun, Y., Bengio, Y., & Hinton, G. (2015) · Nature · doi:10.1038/nature14539 · Cited by 84,126
Bray, M.-A., Singh, S., Han, H., Davis, C. T., Borgeson, B., Hartland, C., Kost-Alimova, M., Gustafsdottir, S. M., Gibson, C. C., & Carpenter, A. E. (2016) · Nature Protocols · doi:10.1038/nprot.2016.105 · Cited by 1,090
Self-citationAnnotated high-throughput microscopy image sets for validation
Ljosa, V., Sokolnicki, K. L., & Carpenter, A. E. (2012) · Nature Methods · doi:10.1038/nmeth.2083 · Cited by 601
Self-citationStanley, S. A., Barczak, A. K., Silvis, M. R., Luo, S. S., Sogi, K., Vokes, M., Bray, M.-A., Carpenter, A. E., Moore, C. B., Siddiqi, N., et al. (2014) · PLoS Pathogens · doi:10.1371/journal.ppat.1003946 · Cited by 251
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Cited by
Cellpose: a generalist algorithm for cellular segmentation
Stringer, C., Wang, T., Michaelos, M., & Pachitariu, M. (2021) · Nature Methods · doi:10.1038/s41592-020-01018-x · Cited by 4,369
A single-cell transcriptomic atlas characterizes ageing tissues in the mouse
The Tabula Muris Consortium, Almanzar, N., Antony, J., Baghel, A. S., Bakerman, I., Bansal, I., Barres, B. A., Beachy, P. A., Berdnik, D., Bilen, B., et al. (2020) · Nature · doi:10.1038/s41586-020-2496-1 · Cited by 1,247
Deep learning for cellular image analysis
Moen, E., Bannon, D., Kudo, T., Graf, W., Covert, M., & Van Valen, D. (2019) · Nature Methods · doi:10.1038/s41592-019-0403-1 · Cited by 1,225
Best practices for single-cell analysis across modalities
Heumos, L., Schaar, A. C., Lance, C., Litinetskaya, A., Drost, F., Zappia, L., Lücken, M. D., Strobl, D. C., Henao, J., Curion, F., et al. (2023) · Nature Reviews Genetics · doi:10.1038/s41576-023-00586-w · Cited by 1,051
Zhao, Z., Chen, X., Dowbaj, A. M., Sljukic, A., Bratlie, K., Lin, L., Fong, E. L. S., Balachander, G. M., Chen, Z., Soragni, A., et al. (2022) · Nature Reviews Methods Primers · doi:10.1038/s43586-022-00174-y · Cited by 1,082
Metadata
- Authors
- McQuin, C., Goodman, A., Chernyshev, V., Kamentsky, L., Cimini, B. A., Karhohs, K. W., Doan, M., Ding, L., Rafelski, S. M., Thirstrup, D., Wiegraebe, W., Singh, S., Becker, T., Caicedo, J. C., & Carpenter, A. E.
- Venue
- PLOS Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2018-07-03
- Volume
- 16
- Issue
- 7
- Pages
- e2005970
- ISSN
- 1544-9173 (ISSN-L)
- 1545-7885
- OpenAlex
- W2811106513
- Cited by
- 1,825
- References
- 6
- FWCI
- 90.93
- Type
- journal article
- Language
- en
- Open access
- gold
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