ArticleNature cell biology2021
Label-free multiplexed microtomography of endogenous subcellular dynamics using generalizable deep learning.
Article in Nature cell biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers.
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Who cites it
54 citing papers in PubMed.
- Broadband backscattering confocal microscopy enables label-free 3D live cell nanoscale sensitive imaging.Science advances · 2026Article
- Optical diffraction tomographic microscopy: a cutting-edge label-free three-dimensional bioimaging.Biophysics reports · 2026Article
- Structural, Compositional, and Dielectric State Profiling in Label-Free Single-Cell Monitoring.Small methods · 2026Review
- Cell context-dependent in silico organelle localization in label-free microscopy images.Nature methods · 2026Article
- Temporal variance mapping with machine learning for label-free 3D chromatin imaging using optical interferometric microscopy.Biomedical optics express · 2026Article
- Self-Driving Microscopes: AI Meets Super-Resolution Microscopy.Small methods · 2026Review
- On the importance of simultaneous label-free multimodal nonlinear optical imaging for biomedical applications.APL photonics · 2025Article
- A correlative quantitative phase contrast and fluorescence super-resolution microscope for imaging molecules in their cellular context.bioRxiv : the preprint server for biology · 2025Article
- On the utility of virtual staining for downstream applications as it relates to task network capacity.Biomedical optics express · 2025Article
- Lightweight and precise cell classification based on holographic tomography-derived refractive index point cloud.Journal of biomedical optics · 2025Article
- Review
- Drug-Induced Reversible Lysosomal Changes Tracked in Live Cells by Holo-Tomographic Flow Cytometry.ACS nano · 2025Article
- Triple-effect correction for Cell Painting data with contrastive and domain-adversarial learning.Nature communications · 2025Article
- From genotype to phenotype: decoding mutations in blasts by holo-tomographic flow cytometry.Light, science & applications · 2025Article
- Holotomographic microscopy reveals label-free quantitative dynamics of endothelial cells during endothelialization.European journal of cell biology · 2025Article
- Label-free mitochondrial dynamics analysis during cell death using organelle-specific phase contrast microscopy (OS-PCM).Biomedical optics express · 2025Article
- Deep learning-enabled filter-free fluorescence microscope.Science advances · 2025Article
- Measuring Molecular Mass Densities at Subcellular Resolution Using Optical Diffraction Tomography.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Unsupervised inter-domain transformation for virtually stained high-resolution mid-infrared photoacoustic microscopy using explainable deep learning.Nature communications · 2024Article
- Long-term three-dimensional high-resolution imaging of live unlabeled small intestinal organoids via low-coherence holotomography.Experimental & molecular medicine · 2024Article
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Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Simultaneous imaging of various facets of intact biological systems across multiple spatiotemporal scales is a long-standing goal in biology and medicine, for which progress is hindered by limits of conventional imaging modalities. Here we propose using the refractive index (RI), an intrinsic quantity governing light-matter interaction, as a means for such measurement. We show that major endogenous subcellular structures, which are conventionally accessed via exogenous fluorescence labelling, are encoded in three-dimensional (3D) RI tomograms. We decode this information in a data-driven manner, with a deep learning-based model that infers multiple 3D fluorescence tomograms from RI measurements of the corresponding subcellular targets, thereby achieving multiplexed microtomography. This approach, called RI2FL for refractive index to fluorescence, inherits the advantages of both high-specificity fluorescence imaging and label-free RI imaging. Importantly, full 3D modelling of absolute and unbiased RI improves generalization, such that the approach is applicable to a broad range of new samples without retraining to facilitate immediate applicability. The performance, reliability and scalability of this technology are extensively characterized, and its various applications within single-cell profiling at unprecedented scales (which can generate new experimentally testable hypotheses) are demonstrated.
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