ArticleBiomedical optics express2022
Active image optimization for lattice light sheet microscopy in thick samples.
Article in Biomedical optics express, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- A practical guide to light-sheet microscopy for nanoscale imaging: Looking beyond the cell.Journal of applied physics · 2024Article
- Applications of Lightsheet Fluorescence Microscopy by High Numerical Aperture Detection Lens.The journal of physical chemistry. B · 2024Review
- Posterior approach to correct for focal plane offsets in lattice light-sheet structured illumination microscopy.Journal of biomedical optics · 2024Article
- Introduction to the Optics and the Brain 2023 feature issue.Biomedical optics express · 2024Article
- Understanding the nervous system: lessons from Frontiers in Neurophotonics.Neurophotonics · 2024Review
- Super-resolution microscopy to study membrane nanodomains and transport mechanisms in the plasma membrane.Frontiers in molecular biosciences · 2024Review
- Light-sheets and smart microscopy, an exciting future is dawning.Communications biology · 2023Review
- Introduction to the Feature Issue on Adaptive Optics for Biomedical Applications.Biomedical optics express · 2023Article
Corrections and comments
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Authors and funding
8 authors.
Funding
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Abstract
Lattice light-sheet microscopy (LLSM) is a very efficient technique for high resolution 3D imaging of dynamic phenomena in living biological samples. However, LLSM imaging remains limited in depth due to optical aberrations caused by sample-based refractive index mismatch. Here, we propose a simple and low-cost active image optimization (AIO) method to recover high resolution imaging inside thick biological samples. AIO is based on (1) a light-sheet autofocus step (AF) followed by (2) an adaptive optics image-based optimization. We determine the optimum AIO parameters to provide a fast, precise and robust aberration correction on biological samples. Finally, we demonstrate the performances of our approach on sub-micrometric structures in brain slices and plant roots.
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Registered trials
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