ArticleJournal of biophotonics2019
Multi-ATOM: Ultrahigh-throughput single-cell quantitative phase imaging with subcellular resolution.
Article in Journal of biophotonics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Generalizable morphological profiling of cells by interpretable unsupervised learning.Nature communications · 2025Article
- Imaging flow cytometry with a real-time throughput beyond 1,000,000 events per second.Light, science & applications · 2025Article
- Information-Distilled Generative Label-Free Morphological Profiling Encodes Cellular Heterogeneity.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Morphological profiling by high-throughput single-cell biophysical fractometry.Communications biology · 2023Article
- Finding intracellular lipid droplets from the single-cell biolens' signature in a holographic flow-cytometry assay.Biomedical optics express · 2022Article
- Comprehensive single-shot biophysical cytometry using simultaneous quantitative phase imaging and Brillouin spectroscopy.Scientific reports · 2022Article
- Molecular determinants of intrinsic cellular stiffness in health and disease.Biophysical reviews · 2022Review
- A review of microscopic cell imaging and neural network recognition for synergistic cyanobacteria identification and enumeration.Analytical sciences : the international journal of the Japan Society for Analytical Chemistry · 2022Review
- Machine learning-based approaches for identifying human blood cells harboring CRISPR-mediated fetal chromatin domain ablations.Scientific reports · 2022Article
- Multi-angle pulse shape detection of scattered light in flow cytometry for label-free cell cycle classification.Communications biology · 2021Article
- High-speed laser-scanning biological microscopy using FACED.Nature protocols · 2021Article
- Cell morphology-based machine learning models for human cell state classification.NPJ systems biology and applications · 2021Article
- Photonic technologies for liquid biopsies: recent advances and open research challenges.Laser & photonics reviews · 2021Article
- PARC: ultrafast and accurate clustering of phenotypic data of millions of single cells.Bioinformatics (Oxford, England) · 2020Article
- Quantitative scoring of epithelial and mesenchymal qualities of cancer cells using machine learning and quantitative phase imaging.Journal of biomedical optics · 2020Article
- Multi-ATOM: Ultrahigh-throughput single-cell quantitative phase imaging with subcellular resolution.Journal of biophotonics · 2019Article
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13 authors.
Funding
Abstract
A growing body of evidence has substantiated the significance of quantitative phase imaging (QPI) in enabling cost-effective and label-free cellular assays, which provides useful insights into understanding the biophysical properties of cells and their roles in cellular functions. However, available QPI modalities are limited by the loss of imaging resolution at high throughput and thus run short of sufficient statistical power at the single-cell precision to define cell identities in a large and heterogeneous population of cells-hindering their utility in mainstream biomedicine and biology. Here we present a new QPI modality, coined multiplexed asymmetric-detection time-stretch optical microscopy (multi-ATOM) that captures and processes quantitative label-free single-cell images at ultrahigh throughput without compromising subcellular resolution. We show that multi-ATOM, based upon ultrafast phase-gradient encoding, outperforms state-of-the-art QPI in permitting robust phase retrieval at a QPI throughput of >10 000 cell/sec, bypassing the need for interferometry which inevitably compromises QPI quality under ultrafast operation. We employ multi-ATOM for large-scale, label-free, multivariate, cell-type classification (e.g. breast cancer subtypes, and leukemic cells vs peripheral blood mononuclear cells) at high accuracy (>94%). Our results suggest that multi-ATOM could empower new strategies in large-scale biophysical single-cell analysis with applications in biology and enriching disease diagnostics.
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