ArticleApplied physics letters2013
Optical sectioning by wide-field photobleaching imprinting microscopy.
Article in Applied physics letters, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The trial behind it
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Who cites it
6 citing papers in PubMed.
- Advances in Optical Contrast Agents for Medical Imaging: Fluorescent Probes and Molecular Imaging.Journal of imaging · 2025Review
- High-Throughput, Low Background, and Wide-Field Microscopy by Flat-Field Photobleaching Imprinting Microscopy.Chemical & biomedical imaging · 2023Article
- Acoustic transmissive cloaking with adjustable capacity to the incident direction.Microsystems & nanoengineering · 2022Article
- Photobleaching Imprinting Enhanced Background Rejection in Line-Scanning Temporal Focusing Microscopy.Frontiers in chemistry · 2020Article
- Graphene laminated gold bipyramids as sensitive detection platforms for antibiotic molecules.Chemical communications (Cambridge, England) · 2015Article
- Reversibly switchable fluorescence microscopy with enhanced resolution and image contrast.Journal of biomedical optics · 2014Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
We present a generic wide-field optical sectioning scheme, photobleaching imprinting microscopy (PIM), for depth-resolved cross-sectional fluorescence imaging. Wide-field PIM works by extracting a nonlinear component that depends on the excitation fluence as a result of photobleaching-induced fluorescence decay. Since no specific fluorescent dyes or illumination modules are required, wide-field PIM is easy to implement on a standard microscope. Moreover, wide-field PIM is superior to deconvolution microscopy in removing background fluorescence, yielding a six-fold improvement in image contrast.
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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.