ArticleNature communications2022
All-fiber high-speed image detection enabled by deep learning.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed, 93 citations in OpenAlex.
- Spatiotemporal all-optical diffractive neural networks empowered by spatiotemporal light field manipulation.Light, science & applications · 2026Article
- M3-RGB: An Imaging Sensor System Using Multicore, Multimode Optical Fiber and Neural Networks.Sensors (Basel, Switzerland) · 2026Article
- Online high speed detection method for end face quality of cored filter rods under complex conditions.Scientific reports · 2025Article
- Deep empirical neural network for optical phase retrieval over a scattering medium.Nature communications · 2025Article
- Artificial Intelligence in Biomedical Sciences: A Scoping Review.British journal of biomedical science · 2025Article
- Mid-infrared single-photon upconversion spectroscopy enabled by nonlocal wavelength-to-time mapping.Science advances · 2024Article
- Non-orthogonal optical multiplexing empowered by deep learning.Nature communications · 2024Article
- Photonic Bound States in the Continuum in Nanostructures.Materials (Basel, Switzerland) · 2023Review
- Spatiotemporal mode-locking and dissipative solitons in multimode fiber lasers.Light, science & applications · 2023Review
- Optical Fibre-Based Sensors-An Assessment of Current Innovations.Biosensors · 2023Review
- Robust real-time imaging through flexible multimode fibers.Scientific reports · 2023Article
- SMD-YOLO: An efficient and lightweight detection method for mask wearing status during the COVID-19 pandemic.Computer methods and programs in biomedicine · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ultra-high-speed imaging serves as a foundation for modern science. While in biomedicine, optical-fiber-based endoscopy is often required for in vivo applications, the combination of high speed with the fiber endoscopy, which is vital for exploring transient biomedical phenomena, still confronts some challenges. We propose all-fiber imaging at high speeds, which is achieved based on the transformation of two-dimensional spatial information into one-dimensional temporal pulsed streams by leveraging high intermodal dispersion in a multimode fiber. Neural networks are trained to reconstruct images from the temporal waveforms. It can not only detect content-aware images with high quality, but also detect images of different kinds from the training images with slightly reduced quality. The fiber probe can detect micron-scale objects with a high frame rate (15.4 Mfps) and large frame depth (10,000). This scheme combines high speeds with high mechanical flexibility and integration and may stimulate future research exploring various phenomena in vivo.
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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.