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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...

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Related Experiment Video

Updated: Mar 24, 2026

Multi-color Localization Microscopy of Single Membrane Proteins in Organelles of Live Mammalian Cells

Multi-color Localization Microscopy of Single Membrane Proteins in Organelles of Live Mammalian Cells

Published on: June 30, 2018

SuReSim: simulating localization microscopy experiments from ground truth models.

Varun Venkataramani¹, Frank Herrmannsdörfer¹, Mike Heilemann^1,2

¹Institute for Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany.

|March 2, 2016

Summary

This summary is machine-generated.

Designing super-resolution microscopy experiments is challenging. SuReSim software simulates imaging data, enabling researchers to optimize experimental parameters for better super-resolution fluorescence microscopy outcomes.

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Last Updated: Mar 24, 2026

Multi-color Localization Microscopy of Single Membrane Proteins in Organelles of Live Mammalian Cells

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Area of Science:

Biophysics
Cell Biology
Microscopy

Background:

Super-resolution fluorescence microscopy is a powerful research tool.
Experiment design and validation pose significant challenges for researchers.
Optimizing imaging parameters is crucial for scientifically rigorous super-resolution studies.

Purpose of the Study:

To introduce SuReSim, a novel software tool for simulating super-resolution microscopy data.
To enable systematic exploration of experimental parameter effects on imaging outcomes.
To aid researchers in designing and validating super-resolution experiments.

Main Methods:

Development of SuReSim software.
Simulation of localization data for arbitrary 3D structures.
Representation of structures using ground truth models.

Main Results:

SuReSim allows simulation of localization data from 3D models.
Users can systematically investigate the impact of varying experimental parameters.
The software facilitates the prediction of potential imaging outcomes.

Conclusions:

SuReSim provides a valuable platform for super-resolution experiment design.
The tool aids in overcoming challenges in validating super-resolution imaging.
SuReSim supports scientifically rigorous and technically feasible research using super-resolution microscopy.