ArticleNature biotechnology2023
Real-time denoising enables high-sensitivity fluorescence time-lapse imaging beyond the shot-noise limit.
Article in Nature biotechnology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers.
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Who cites it
72 citing papers in PubMed.
- Extended field-of-view two-photon imaging in the deep brain of freely behaving mice using lightweight microfabricated corrective optics.Science advances · 2026Article
- Physics-informed self-supervised denoising for fluorescence microscopy via structure and intensity priors.iScience · 2026Article
- Cellular and molecular coding of habit-driven behavior in the dorsal raphe nucleus.bioRxiv : the preprint server for biology · 2026Article
- NIR-II squeezed light-field microscopy enables high-speed volumetric imaging of deep-tissue dynamicsbioRxiv : the preprint server for biology · 2026Article
- Rapid robust high-fidelity 3D neuronal extraction from multiview calcium imaging datasets.Nature methods · 2026Article
- Distributed cortical learning through LEC-mediated γ-synchrony.Nature communications · 2026Article
- Self-supervised image denoising and restoration method for atomic force microscopy.Nature communications · 2026Article
- CALIPERS: Cell cycle-aware live imaging for phenotyping experiments and regeneration studies.Nature communications · 2026Article
- FACED 2.0 enables large-scale voltage and calcium imaging in vivo.Nature methods · 2026Article
- Physics-paired stimulated Raman scattering microscopy enables label-free phenotyping of lipid droplets 3D motility in live cells.Light, science & applications · 2026Article
- High-fidelity fast fluorescence lifetime imaging by event-based denoising.Nature biotechnology · 2026Article
- Artificial Intelligence for Discovery in Life Sciences.Bioconjugate chemistry · 2026Review
- Physics-guided self-supervised learning for high-fidelity reconstruction in live-cell imaging.Npj imaging · 2026Article
- Tunable acoustic rotation for deep biophysical phenotyping of preclinical Alzheimer's disease.Materials today. Bio · 2026Article
- Aberration-aware 3D localization microscopy via self-supervised neural-physics learning.Nature communications · 2026Article
- Unsupervised transfer learning enables multi-animal tracking without training annotation.Nature methods · 2026Article
- Enhancing biomedical optical volumetric imaging via self-supervised orthogonal learning.Science advances · 2026Article
- Pushing the limits of fluorescence imaging with a restoration neural network aggregating large-view statistics.Nature communications · 2026Article
- Green channel-informed collaborative filtering for high-fidelity laser speckle contrast imaging in dual-display laparoscopy.Biomedical optics express · 2026Article
- Noise-tolerant correlated coincidence imaging based on supercorrelated light at 1550 nm.Science advances · 2026Article
12 more citing papers are in PubMed but not listed here.
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21 authors.
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Abstract
A fundamental challenge in fluorescence microscopy is the photon shot noise arising from the inevitable stochasticity of photon detection. Noise increases measurement uncertainty and limits imaging resolution, speed and sensitivity. To achieve high-sensitivity fluorescence imaging beyond the shot-noise limit, we present DeepCAD-RT, a self-supervised deep learning method for real-time noise suppression. Based on our previous framework DeepCAD, we reduced the number of network parameters by 94%, memory consumption by 27-fold and processing time by a factor of 20, allowing real-time processing on a two-photon microscope. A high imaging signal-to-noise ratio can be acquired with tenfold fewer photons than in standard imaging approaches. We demonstrate the utility of DeepCAD-RT in a series of photon-limited experiments, including in vivo calcium imaging of mice, zebrafish larva and fruit flies, recording of three-dimensional (3D) migration of neutrophils after acute brain injury and imaging of 3D dynamics of cortical ATP release. DeepCAD-RT will facilitate the morphological and functional interrogation of biological dynamics with a minimal photon budget.
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