ArticleNature methods2021
Deep learning-enhanced light-field imaging with continuous validation.
Article in Nature methods, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.
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Who cites it
50 citing papers in PubMed.
- Bridging annotated microscopy imaging data and analysis method development for scientific discovery.Patterns (New York, N.Y.) · 2026Review
- Deep Learning Integration in Optical Microscopy: Advancements and Applications.Microscopy research and technique · 2026Review
- High-fidelity intravital imaging of biological dynamics with latent-space-enhanced digital adaptive optics.Nature biotechnology · 2026Article
- Patch deconvolution for Fourier light-field microscopy.Biophysical journal · 2026Article
- A Comprehensive Review of Nuclear Mechanics: Advances, Disease Relevance, Methodologies, and AI Applications.Cell biochemistry and biophysics · 2026Review
- Lightweight CycleGAN models for cross-modality image transformation and experimental quality assessment in fluorescence microscopy.Biomedical optics express · 2026Article
- Intravital mesoscale optical imaging: challenges, techniques, and future perspectives.Biophysics reports · 2026Article
- Snapshot 3D at the speed frontier: redefining light-field microscopy for neuroimaging.PhotoniX · 2026Article
- Volumetric localization microscopy with deep learning.Nature communications · 2025Article
- Light-field deep learning enables high-throughput, scattering-mitigated calcium imaging.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Kilohertz volumetric imaging of in vivo dynamics using squeezed light field microscopy.Nature methods · 2025Article
- Physics-driven self-supervised learning for fast high-resolution robust 3D reconstruction of light-field microscopy.Nature methods · 2025Article
- Real-time and universal network for volumetric imaging from microscale to macroscale at high resolution.Light, science & applications · 2025Article
- Review
- Ultrafast optical imaging techniques for exploring rapid neuronal dynamics.Neurophotonics · 2025Review
- Volumetric voltage imaging of neuronal populations in the mouse brain by confocal light-field microscopy.Nature methods · 2024Article
- Efficient high-resolution fluorescence projection imaging over an extended depth of field through optical hardware and deep learning optimizations.Biomedical optics express · 2024Article
- Bioluminescence as a functional tool for visualizing and controlling neuronal activityNeurophotonics · 2024Article
- Light-field flow cytometry for high-resolution, volumetric and multiparametric 3D single-cell analysis.Nature communications · 2024Article
- Harnessing artificial intelligence to reduce phototoxicity in live imaging.Journal of cell science · 2024Article
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Visualizing dynamic processes over large, three-dimensional fields of view at high speed is essential for many applications in the life sciences. Light-field microscopy (LFM) has emerged as a tool for fast volumetric image acquisition, but its effective throughput and widespread use in biology has been hampered by a computationally demanding and artifact-prone image reconstruction process. Here, we present a framework for artificial intelligence-enhanced microscopy, integrating a hybrid light-field light-sheet microscope and deep learning-based volume reconstruction. In our approach, concomitantly acquired, high-resolution two-dimensional light-sheet images continuously serve as training data and validation for the convolutional neural network reconstructing the raw LFM data during extended volumetric time-lapse imaging experiments. Our network delivers high-quality three-dimensional reconstructions at video-rate throughput, which can be further refined based on the high-resolution light-sheet images. We demonstrate the capabilities of our approach by imaging medaka heart dynamics and zebrafish neural activity with volumetric imaging rates up to 100 Hz.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.