ArticleBiomedical optics express2020
Live-SIMBA: an ImageJ plug-in for the universal and accelerated single molecule-guided Bayesian localization super resolution microscopy (SIMBA) method.
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 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
- Fluorescence fluctuation-based super-resolution microscopy: Basic concepts for an easy start.Journal of microscopy · 2022Review
- From whole organism to ultrastructure: progress in axonal imaging for decoding circuit development.Development (Cambridge, England) · 2021Review
- DETECTOR: structural information guided artifact detection for super-resolution fluorescence microscopy image.Biomedical optics express · 2021Article
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Authors and funding
7 authors.
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Abstract
Live-cell super-resolution fluorescence microscopy techniques allow biologists to observe subcellular structures, interactions and dynamics at the nanoscale level. Among of them, single molecule-guided Bayesian localization super resolution microscopy (SIMBA) and its derivatives produce an appropriate 50 nm spatial resolution and a 0.1-2s temporal resolution in living cells with simple off-the-shelf total internal reflection fluorescence (TIRF) equipment. However, SIMBA and its derivatives are limited by the requirement for dual-channel dataset or single-channel dataset with special design, the time-consuming calculation for extended field of view and the lack of real-time visualization tool. Here, we propose a universal and accelerated SIMBA ImageJ plug-in, Live-SIMBA, for time-series analysis in living cells. Live-SIMBA circumvents the requirement of dual-channel dataset using intensity-based sampling algorithm and improves the computing speed using multi-core parallel computing technique. Live-SIMBA also better resolves the weak signals inside the specimens with adjustable background estimation and distance-threshold filter. With improved fidelity on reconstructed structures, greatly accelerated computation, and real-time visualization, Live-SIMBA demonstrates its extended capabilities in live-cell super-resolution imaging.
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Registered trials
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