A high-density 3D localization algorithm for stochastic optical reconstruction microscopy
Open Access
- 1 January 2012
- journal article
- research article
- Published by Springer Science and Business Media LLC in Optical Nanoscopy
- Vol. 1 (1), 6
- https://doi.org/10.1186/2192-2853-1-6
Abstract
Stochastic optical reconstruction microscopy (STORM) and related methods achieves sub-diffraction-limit image resolution through sequential activation and localization of individual fluorophores. The analysis of image data from these methods has typically been confined to the sparse activation regime where the density of activated fluorophores is sufficiently low such that there is minimal overlap between the images of adjacent emitters. Recently several methods have been reported for analyzing higher density data, allowing partial overlap between adjacent emitters. However, these methods have so far been limited to two-dimensional imaging, in which the point spread function (PSF) of each emitter is assumed to be identical. In this work, we present a method to analyze high-density super-resolution data in three dimensions, where the images of individual fluorophores not only overlap, but also have varying PSFs that depend on the z positions of the fluorophores. This approach accurately analyzed data sets with an emitter density five times higher than previously possible with sparse emitter analysis algorithms. We applied this algorithm to the analysis of data sets taken from membrane-labeled retina and brain tissues which contain a high-density of labels, and obtained substantially improved super-resolution image quality.Keywords
This publication has 25 references indexed in Scilit:
- Statistical Deconvolution for Superresolution Fluorescence MicroscopyBiophysical Journal, 2012
- Faster STORM using compressed sensingNature Methods, 2012
- Bayesian localization microscopy reveals nanoscale podosome dynamicsNature Methods, 2011
- Evaluation of fluorophores for optimal performance in localization-based super-resolution imagingNature Methods, 2011
- Breaking the Diffraction Barrier: Super-Resolution Imaging of CellsCell, 2010
- Fast, single-molecule localization that achieves theoretically minimum uncertaintyNature Methods, 2010
- Optimized localization analysis for single-molecule tracking and super-resolution microscopyNature Methods, 2010
- Three-dimensional, single-molecule fluorescence imaging beyond the diffraction limit by using a double-helix point spread functionProceedings of the National Academy of Sciences of the United States of America, 2009
- Imaging Intracellular Fluorescent Proteins at Nanometer ResolutionScience, 2006
- Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM)Nature Methods, 2006