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Super-resolution Fluorescence Microscopy

Super-resolution Fluorescence Microscopy

Super-resolution fluorescence microscopy (SRFM) provides a better resolution than conventional fluorescence microscopy by reducing the point spread function (PSF). PSF is the light intensity distribution from a point that causes it to appear blurred. Due to PSF, each fluorescing point appears bigger than its actual size, and it is the PSF interference of nearby fluorophores that causes the blurred image. Various approaches to achieving higher resolution through SRFM have recently been developed.

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Related Experiment Video

Updated: May 11, 2026

Conventional BODIPY Conjugates for Live-Cell Super-Resolution Microscopy and Single-Molecule Tracking

Conventional BODIPY Conjugates for Live-Cell Super-Resolution Microscopy and Single-Molecule Tracking

Published on: June 8, 2020

Real-time analysis and visualization for single-molecule based super-resolution microscopy.

Adel Kechkar¹, Deepak Nair, Mike Heilemann

¹Interdisciplinary Institute for Neuroscience, University of Bordeaux, Bordeaux, France.

|May 7, 2013

Summary

This summary is machine-generated.

This study presents a fast, accurate method for 3D localization in super-resolution microscopy using real-time reconstruction and feedback control. The technique enhances efficiency and feasibility for analyzing single fluorescent molecules.

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Last Updated: May 11, 2026

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Area of Science:

Microscopy
Biophysics
Optical Imaging

Background:

Super-resolution microscopy enables imaging beyond the diffraction limit.
Accurate localization of single fluorescent emitters is crucial for super-resolution imaging.
Current localization methods can be time-consuming, limiting acquisition speed.

Purpose of the Study:

To develop a functional method for real-time, accurate multidimensional localization of fluorescent emitters.
To improve the efficiency and feasibility of localization-based super-resolution microscopy.
To enable high-speed imaging without compromising localization accuracy.

Main Methods:

A wavelet segmentation algorithm combined with Gaussian fitting for 3D localization.
Implementation utilizing both CPU and GPU for accelerated processing.
Integration of automatic feedback control for optimal molecule density management.
Compatibility with high frame rate EM-CCD cameras.

Main Results:

Demonstrated a functional method for real-time reconstruction of emitter positions.
Achieved accurate multidimensional localization without compromising accuracy.
Enabled high frame rate acquisition compatible with EM-CCD cameras.
Significantly improved the efficiency and feasibility of super-resolution microscopy.

Conclusions:

The developed method offers a significant advancement in real-time super-resolution microscopy.
Automatic feedback control and efficient algorithms enhance data acquisition speed and reliability.
This approach makes super-resolution microscopy more accessible and practical for various applications.