ArticleJournal of biomedical optics2021
Accelerating 3D single-molecule localization microscopy using blind sparse inpainting.
Article in Journal of biomedical optics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Enhancing ultra-high density single-molecule localization with deep spatiotemporal networks.Biomedical optics express · 2025Article
- Deep learning-based spectroscopic single-molecule localization microscopy.Journal of biomedical optics · 2024Article
- From whole organism to ultrastructure: progress in axonal imaging for decoding circuit development.Development (Cambridge, England) · 2021Review
- Automated and semi-automated enhancement, segmentation and tracing of cytoskeletal networks in microscopic images: A review.Computational and structural biotechnology journal · 2021Review
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Authors and funding
5 authors.
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Abstract
significanceSingle-molecule localization-based super-resolution microscopy has enabled the imaging of microscopic objects beyond the diffraction limit. However, this technique is limited by the requirements of imaging an extremely large number of frames of biological samples to generate a super-resolution image, thus requiring a longer acquisition time. Additionally, the processing of such a large image sequence leads to longer data processing time. Therefore, accelerating image acquisition and processing in single-molecule localization microscopy (SMLM) has been of perennial interest.
aimTo accelerate three-dimensional (3D) SMLM imaging by leveraging a computational approach without compromising the resolution. APPROACH: We used blind sparse inpainting to reconstruct high-density 3D images from low-density ones. The low-density images are generated using much fewer frames than usually needed, thus requiring a shorter acquisition and processing time. Therefore, our technique will accelerate 3D SMLM without changing the existing standard SMLM hardware system and labeling protocol.
resultsThe performance of the blind sparse inpainting was evaluated on both simulation and experimental datasets. Superior reconstruction results of 3D SMLM images using up to 10-fold fewer frames in simulation and up to 50-fold fewer frames in experimental data were achieved.
conclusionsWe demonstrate the feasibility of fast 3D SMLM imaging leveraging a computational approach to reduce the number of acquired frames. We anticipate our technique will enable future real-time live-cell 3D imaging to investigate complex nanoscopic biological structures and their functions.
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