ArticleCommunications biology2021
Parameter-free rendering of single-molecule localization microscopy data for parameter-free resolution estimation.
Article in Communications biology, 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.
- Direct single-molecule detection and super-resolution imaging with a low-cost portable smartphone-based microscope.Nature communications · 2025Article
- Resolution assessment of super-resolution microscopy imaging: structural and technical dependencies for cell biology.Cytotechnology · 2025Article
- Closing the multichannel gap through computational reconstruction of interaction in super-resolution microscopy.Patterns (New York, N.Y.) · 2025Review
- Fluorescence nanoscopy at the sub-10 nm scale.Biophysical reviews · 2021Review
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Authors and funding
3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Localization microscopy is a super-resolution imaging technique that relies on the spatial and temporal separation of blinking fluorescent emitters. These blinking events can be individually localized with a precision significantly smaller than the classical diffraction limit. This sub-diffraction localization precision is theoretically bounded by the number of photons emitted per molecule and by the sensor noise. These parameters can be estimated from the raw images. Alternatively, the resolution can be estimated from a rendered image of the localizations. Here, we show how the rendering of localization datasets can influence the resolution estimation based on decorrelation analysis. We demonstrate that a modified histogram rendering, termed bilinear histogram, circumvents the biases introduced by Gaussian or standard histogram rendering. We propose a parameter-free processing pipeline and show that the resolution estimation becomes a function of the localization density and the localization precision, on both simulated and state-of-the-art experimental datasets.
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