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Super-resolution Fluorescence Microscopy

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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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Updated: Oct 19, 2025

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

Sub-diffraction error mapping for localisation microscopy images.

Richard J Marsh¹, Ishan Costello¹, Mark-Alexander Gorey¹

¹Randall Centre for Cell & Molecular Biophysics, Guy's Campus, King's College London, London, UK.

Nature Communications

|September 24, 2021

Summary

This summary is machine-generated.

Assessing super-resolution microscopy image quality is difficult, especially with overlapping emitters. A new method, HAWKMAN, uses Haar wavelet kernel analysis (HAWK) to reliably map and quantify reconstruction biases and artefacts in crowded fields.

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Last Updated: Oct 19, 2025

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Published on: June 30, 2018

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Area of Science:

Super-resolution microscopy
Image analysis
Biophysics

Background:

Assessing localisation microscopy image quality is challenging.
Emitter overlap in live-cell imaging causes common algorithmic biases and errors.
Existing methods struggle with high emitter densities.

Purpose of the Study:

To develop a general approach for assessing the reliability of localisation microscopy data.
To map and quantify reconstruction bias and artefacts.
To overcome limitations of intensity-based comparisons.

Main Methods:

Utilized Haar wavelet kernel analysis (HAWK) to generate an unbiased reference image.
Applied HAWK to localisation microscopy data analysis.
Developed the HAWK Method for the Assessment of Nanoscopy (HAWKMAN).

Main Results:

HAWKMAN enables unbiased mapping and quantification of reconstruction bias and artefacts.
The method is effective even with significant emitter overlap (crowded fields).
Structural artefacts can be mapped independently of localisation algorithm nonlinearity.

Conclusions:

HAWKMAN provides a general and reliable method for assessing localisation microscopy data quality.
This approach is crucial for accurate interpretation of live-cell imaging data.
The method enhances the trustworthiness of super-resolution microscopy results.