ArticlePhysical review letters2012
Estimation theoretic measure of resolution for stochastic localization microscopy.
Article in Physical review letters, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Quantitative Single-Molecule Localization Microscopy.Annual review of biophysics · 2023Review
- A systematic study on the use of multifunctional nanodiamonds for neuritogenesis and super-resolution imaging.Biomaterials research · 2023Article
- The Decade of Super-Resolution Microscopy of the Presynapse.Frontiers in synaptic neuroscience · 2020Review
- Solid immersion microscopy images cells under cryogenic conditions with 12 nm resolution.Communications biology · 2019Article
- Navigating challenges in the application of superresolution microscopy.The Journal of cell biology · 2017Review
- High-Resolution Group Quantization Phase Processing Method in Radio Frequency Measurement Range.Scientific reports · 2016Article
- High-density three-dimensional localization microscopy across large volumes.Nature methods · 2016Article
- Sparse deconvolution of high-density super-resolution images.Scientific reports · 2016Article
- Closed-loop and activity-guided optogenetic control.Neuron · 2015Review
- A simple method to estimate the average localization precision of a single-molecule localization microscopy experiment.Histochemistry and cell biology · 2014Article
- Precisely and accurately localizing single emitters in fluorescence microscopy.Nature methods · 2014Review
- Fluorophore localization algorithms for super-resolution microscopy.Nature methods · 2014Review
- DNA origami-based standards for quantitative fluorescence microscopy.Nature protocols · 2014Article
- Fluorescence nanoscopy. Methods and applications.Journal of chemical biology · 2013Review
- Measuring image resolution in optical nanoscopy.Nature methods · 2013Article
- Development in the STORM.Developmental cell · 2012Review
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3 authors.
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Abstract
One approach to super-resolution fluorescence microscopy, termed stochastic localization microscopy, relies on the nanometer scale spatial localization of individual fluorescent emitters that stochastically label specific features of the specimen. The precision of emitter localization is an important determinant of the resulting image resolution but is insufficient to specify how well the derived images capture the structure of the specimen. We address this deficiency by considering the inference of specimen structure based on the estimated emitter locations. By using estimation theory, we develop a measure of spatial resolution that jointly depends on the density of the emitter labels, the precision of emitter localization, and prior information regarding the spatial frequency content of the labeled object. The Nyquist criterion does not set the scaling of this measure with emitter number. Given prior information and a fixed emitter labeling density, our resolution measure asymptotes to a finite value as the precision of emitter localization improves. By considering the present experimental capabilities, this asymptotic behavior implies that further resolution improvements require increases in labeling density above typical current values. Our treatment also yields algorithms to enhance reliable image features. Overall, our formalism facilitates the rigorous statistical interpretation of the data produced by stochastic localization imaging techniques.
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