ArticleBiomedical optics express2020
High-throughput fluorescence microscopy using multi-frame motion deblurring.
Article in Biomedical optics express, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
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Who cites it
5 citing papers in PubMed.
- BlurryScope enables compact, cost-effective scanning microscopy for HER2 scoring using deep learning on blurry images.NPJ digital medicine · 2025Article
- GANscan: continuous scanning microscopy using deep learning deblurring.Light, science & applications · 2022Article
- Self-calibrated 3D differential phase contrast microscopy with optimized illumination.Biomedical optics express · 2022Article
- Deep learning for Alzheimer's disease: Mapping large-scale histological tau protein for neuroimaging biomarker validation.NeuroImage · 2022Article
- Probing pluripotency gene regulatory networks with quantitative live cell imaging.Computational and structural biotechnology journal · 2020Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We demonstrate multi-frame motion deblurring for gigapixel wide-field fluorescence microscopy using fast slide scanning with coded illumination. Our method illuminates the sample with multiple pulses within each exposure, in order to introduce structured motion blur. By deconvolving this known motion sequence from the set of acquired measurements, we recover the object with up to 10× higher SNR than when illuminated with a single pulse (strobed illumination), while performing acquisition at 5× higher frame-rate than a comparable stop-and-stare method. Our coded illumination sequence is optimized to maximize the reconstruction SNR. We also derive a framework for determining when coded illumination is SNR-optimal in terms of system parameters such as source illuminance, noise, and motion stage specifications. This helps system designers to choose the ideal technique for high-throughput microscopy of very large samples.
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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.