ArticleNature methods2023
Bio-friendly long-term subcellular dynamic recording by self-supervised image enhancement microscopy.
Article in Nature methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Towards a systematic understanding of the diverse subtypes, biogenesis and functions of large extracellular vesicles.Nature reviews. Molecular cell biology · 2026Review
- Migrasomes program tissue microenvironment: from physiology to oncology, future perspectives in clinical advances.Journal of the National Cancer Center · 2026Review
- Tunable acoustic rotation for deep biophysical phenotyping of preclinical Alzheimer's disease.Materials today. Bio · 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
- A decade of discovery: tracing the footmarks of migrasomes, unveiling the footprints of cells.Science China. Life sciences · 2026Review
- Intravital mesoscale optical imaging: challenges, techniques, and future perspectives.Biophysics reports · 2026Article
- Migrasomes: a journey from biogenesis to multifaceted roles in health and disease.Biomarker research · 2026Review
- MiniFAST: a sensitive and fast miniaturized microscope forNeurophotonics · 2026Article
- Visualizing intraorganellar ultrastructures, dynamics, and interactions with open-access background-free Lock-in-SIM.Nature communications · 2025Article
- Leveraging spatial-angular redundancy for self-supervised denoising of 3D fluorescence imaging without temporal dependency.Nature communications · 2025Article
- AI-based hardware and software tools in microscopy to boost research in immunology and virology.Frontiers in immunology · 2025Review
- Multi-color fluorescence live-cell imaging in Dictyostelium discoideum.Cell structure and function · 2024Article
- Self-inspired learning for denoising live-cell super-resolution microscopy.Nature methods · 2024Article
- Zero-shot learning enables instant denoising and super-resolution in optical fluorescence microscopy.Nature communications · 2024Article
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Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Fluorescence microscopy has become an indispensable tool for revealing the dynamic regulation of cells and organelles. However, stochastic noise inherently restricts optical interrogation quality and exacerbates observation fidelity when balancing the joint demands of high frame rate, long-term recording and low phototoxicity. Here we propose DeepSeMi, a self-supervised-learning-based denoising framework capable of increasing signal-to-noise ratio by over 12 dB across various conditions. With the introduction of newly designed eccentric blind-spot convolution filters, DeepSeMi effectively denoises images with no loss of spatiotemporal resolution. In combination with confocal microscopy, DeepSeMi allows for recording organelle interactions in four colors at high frame rates across tens of thousands of frames, monitoring migrasomes and retractosomes over a half day, and imaging ultra-phototoxicity-sensitive Dictyostelium cells over thousands of frames. Through comprehensive validations across various samples and instruments, we prove DeepSeMi to be a versatile and biocompatible tool for breaking the shot-noise limit.
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Registered trials
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