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Related Experiment Video

Updated: May 29, 2026

Sample Drift Correction Following 4D Confocal Time-lapse Imaging

Sample Drift Correction Following 4D Confocal Time-lapse Imaging

Published on: April 12, 2014

Sample drift correction in 3D fluorescence photoactivation localization microscopy.

Michael J Mlodzianoski¹, John M Schreiner, Steven P Callahan

¹Department of Cell Biology, Yale School of Medicine, 333 Cedar Street, New Haven, CT 06510, USA.

|September 22, 2011

Summary

This summary is machine-generated.

This study presents a novel method for correcting 3D sample drift in super-resolution microscopy, crucial for accurate imaging. The technique achieves high precision without fiduciary markers, enhancing biological structure analysis.

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Published on: December 1, 2016

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Last Updated: May 29, 2026

Sample Drift Correction Following 4D Confocal Time-lapse Imaging

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Published on: April 12, 2014

Simultaneous Multicolor Imaging of Biological Structures with Fluorescence Photoactivation Localization Microscopy

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Published on: December 9, 2013

Three-dimensional Super Resolution Microscopy of F-actin Filaments by Interferometric PhotoActivated Localization Microscopy (iPALM)

Three-dimensional Super Resolution Microscopy of F-actin Filaments by Interferometric PhotoActivated Localization Microscopy (iPALM)

Published on: December 1, 2016

Area of Science:

Biophysics
Optical Microscopy
Cell Biology

Background:

Super-resolution microscopy offers ten-fold resolution improvement over conventional light microscopy.
Increased resolution amplifies the impact of sample drift, degrading image quality and potentially leading to misinterpretation.
Techniques like FPALM/PALM and STORM are particularly vulnerable due to long acquisition times.

Purpose of the Study:

To develop and validate a method for correcting 3D sample drift in fixed samples.
To achieve drift correction without requiring fiduciary markers or instrument modifications.
To demonstrate the algorithm's performance and practical applicability in super-resolution imaging.

Main Methods:

Calculating the spatial cross-correlation function between subsets of localized particles imaged at different time points.
Applying the cross-correlation analysis to determine and correct for three-dimensional sample movement.
Utilizing simulated structures and real biological samples (mitochondria) for validation.

Main Results:

Achieved drift correction with precision down to approximately 5 nm.
Demonstrated effective correction even when different molecules are imaged in successive frames.
Validated the algorithm's performance across various simulated structures and particle densities.

Conclusions:

The developed algorithm effectively corrects 3D sample drift in super-resolution microscopy.
This method enhances image fidelity and reliability for detailed biological structure analysis.
The approach is practical and applicable to techniques like Biplane FPALM for imaging cellular components.