The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Ghost cytometry
Abstract
Seeing ghosts: In fluorescence-activated cell sorting, characteristic target features are labeled with a specific fluorophore, and cells displaying different fluorophores are sorted. Ota et al. describe a technique called ghost cytometry that allows cell sorting based on the morphology of the cytoplasm, labeled with a single-color fluorophore. The motion of cells relative to a patterned optical structure provides spatial information that is compressed into temporal signals, which are sequentially measured by a single-pixel detector. Images can be reconstructed from this spatial and temporal information, but this is computationally costly. Instead, using machine learning, cells are classified directly from the compressed signals, without reconstructing an image. The method was able to separate morphologically similar cell types in an ultrahigh-speed fluorescence imaging–activated cell sorter. Science , this issue p. 1246
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Single-pixel imaging via compressive sampling
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A New TwIST: Two-Step Iterative Shrinkage/Thresholding Algorithms for Image Restoration
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Whole-Brain Imaging with Single-Cell Resolution Using Chemical Cocktails and Computational Analysis
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Cited by
High-performance medicine: the convergence of human and artificial intelligence
Topol, E. J. (2019) · Nature Medicine · doi:10.1038/s41591-018-0300-7 · Cited by 10,450
Liquid biopsy enters the clinic — implementation issues and future challenges
Ignatiadis, M., Sledge, G. W., & Jeffrey, S. S. (2021) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-020-00457-x · Cited by 1,191
Intelligent Image-Activated Cell Sorting
Nitta, N., Sugimura, T., Isozaki, A., Mikami, H., Hiraki, K., Sakuma, S., Iino, T., Arai, F., Endo, T., Fujiwaki, Y., et al. (2018) · Cell · doi:10.1016/j.cell.2018.08.028 · Cited by 538
High-speed fluorescence image–enabled cell sorting
Schraivogel, D., Kuhn, T. M., Rauscher, B., Rodríguez-Martínez, M., Paulsen, M., Owsley, K., Middlebrook, A., Tischer, C., Ramasz, B., Ordoñez-Rueda, D., et al. (2022) · Science · doi:10.1126/science.abj3013 · Cited by 284
Metadata
- Authors
- Ota, S., Horisaki, R., Kawamura, Y., Ugawa, M., Sato, I., Hashimoto, K., Kamesawa, R., Setoyama, K., Yamaguchi, S., Fujiu, K., Waki, K., & Noji, H.
- Venue
- Science
- Published
- 2018-06-15
- Volume
- 360
- Issue
- 6394
- Pages
- 1246-1251
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W4213078347
- Cited by
- 257
- References
- 27
- FWCI
- 7.99
- Type
- journal article
- Language
- en
- Open access
- closed
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- Ota, S., Horisaki, R., Kawamura, Y., Ugawa, M., Sato, I., Hashimoto, K., Kamesawa, R., Setoyama, K., Yamaguchi, S., Fujiu, K., Waki, K., & Noji, H. (2018). Ghost cytometry. Science. https://doi.org/10.1126/science.aan0096
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