2018
DOI: 10.1016/j.cell.2018.08.028
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Intelligent Image-Activated Cell Sorting

Abstract: A fundamental challenge of biology is to understand the vast heterogeneity of cells, particularly how cellular composition, structure, and morphology are linked to cellular physiology. Unfortunately, conventional technologies are limited in uncovering these relations. We present a machine-intelligence technology based on a radically different architecture that realizes real-time image-based intelligent cell sorting at an unprecedented rate. This technology, which we refer to as intelligent image-activated cell… Show more

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Cited by 444 publications
(371 citation statements)
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References 54 publications
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“…For instance, this label‐free single‐cell imaging approach could be used in conjunction with the existing liquid biopsy strategies for augmenting the cost‐effectiveness of circulating tumor cell detection . Further integrated with high‐throughput image‐activated cell sorting, which becomes increasingly plausible , multi‐ATOM flow cytometry could enrich targeted cell population based on their biophysical phenotypes in real‐time and thus enables downstream biomolecular analysis (e.g., single‐cell genomic or transcriptomic analysis). This could open a new paradigm shift in SCA in which systematic study of complex correlation between biophysical and biomolecular signatures of single cells.…”
Section: Discussionmentioning
confidence: 99%
“…For instance, this label‐free single‐cell imaging approach could be used in conjunction with the existing liquid biopsy strategies for augmenting the cost‐effectiveness of circulating tumor cell detection . Further integrated with high‐throughput image‐activated cell sorting, which becomes increasingly plausible , multi‐ATOM flow cytometry could enrich targeted cell population based on their biophysical phenotypes in real‐time and thus enables downstream biomolecular analysis (e.g., single‐cell genomic or transcriptomic analysis). This could open a new paradigm shift in SCA in which systematic study of complex correlation between biophysical and biomolecular signatures of single cells.…”
Section: Discussionmentioning
confidence: 99%
“…Even if phytoplankton fluorescence patterns can be derived from natural samples, high diversity of species in combination with pigment variability makes it much more difficult to unambiguously identify species. Alternatively, a way to further automate species identification from an IFC without feature selection and instead via deep learning is presented by Nitta et al (66) and Dunker et al (16). In this case, this was done with laboratory-grown cultures.…”
Section: Discussionmentioning
confidence: 99%
“…In this case, this was done with laboratory-grown cultures. Nitta et al (66) presented an approach for intelligent sorting based on a deep learning algorithm with similar high accuracy in real-time, which is a promising step for future technology development. Several new IFC approaches for phytoplankton are emerging (47,63,65) and are based on time-stretch imaging in microfluidic systems (49) or fluorescence microscopy (63,65).…”
Section: Discussionmentioning
confidence: 99%
“…Imaging flow cytometry is a state-of-theart bioanalytical technology that can precisely characterize multiple cellular behaviors including cell internalization, cell cycle, and cell morphology changes in a rapid and high-throughput manner (14)(15)(16)19,20). Imaging flow cytometry is a state-of-theart bioanalytical technology that can precisely characterize multiple cellular behaviors including cell internalization, cell cycle, and cell morphology changes in a rapid and high-throughput manner (14)(15)(16)19,20).…”
Section: Discussionmentioning
confidence: 99%