ArticleScientific reports2019
Fourier transforms for fast and quantitative Laser Speckle Imaging.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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.
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Who cites it
4 citing papers in PubMed.
- Analysis of Dynamic Stability Control of Light Source in Immersion DUV Lithography.Micromachines · 2025Article
- Direct characterization of tissue dynamics with laser speckle contrast imaging.Biomedical optics express · 2022Article
- Quantifying solvent action in oil paint using portable laser speckle imaging.Scientific reports · 2020Article
- Electroplasticization of Liquid Crystal Polymer Networks.ACS applied materials & interfaces · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Laser speckle imaging is a powerful imaging technique that visualizes microscopic motion within turbid materials. At current two methods are widely used to analyze speckle data: one is fast but qualitative, the other quantitative but computationally expensive. We have developed a new processing algorithm based on the fast Fourier transform, which converts raw speckle patterns into maps of microscopic motion and is both fast and quantitative, providing a dynamnic spectrum of the material over a frequency range spanning several decades. In this article we show how to apply this algorithm and how to measure a diffusion coefficient with it. We show that this method is quantitative and several orders of magnitude faster than the existing quantitative method. Finally we harness the potential of this new approach by constructing a portable laser speckle imaging setup that performs quantitative data processing in real-time on a tablet.
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Registered trials
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