Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

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.

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Pediatric Trauma Care Standardization: A Statewide Survey of Trauma Providers and Program Managers.

The Journal of surgical research·2023

Same author

Impact of institutional prophylaxis guidelines on rates of pediatric venous thromboembolism following trauma-A multicenter study from the pediatric trauma society research committee.

The journal of trauma and acute care surgery·2023

Same author

Venous thromboembolic screening in pediatric trauma: A prospective cohort study of risk-stratified ultrasonography.

The journal of trauma and acute care surgery·2022

Same author

Non-melanoma skin cancer segmentation for histopathology dataset.

Data in brief·2021

Same author

Protect Our Kids: a novel program bringing hemorrhage control to schools.

Injury epidemiology·2021

Same author

LLAMA: a robust and scalable machine learning pipeline for analysis of large scale 4D microscopy data: analysis of cell ruffles and filopodia.

BMC bioinformatics·2021

Same journal

1,2-Aminothiol-specific conjugation for dual-color fluorescent labeling via ultrafast TAMM conjugates.

Methods in enzymology·2026

Same journal

Nitrone dipoles in bioorthogonal chemistry applications.

Methods in enzymology·2026

Same journal

Bioorthogonal labeling of sialic acid isomers for detection of glycoconjugates by mass spectrometry imaging and microscopy.

Methods in enzymology·2026

Same journal

Bioorthogonal photocatalytic proximity labeling for quantitative mapping of cell-cell interactions.

Methods in enzymology·2026

Same journal

inCu-click: Enabling copper-catalyzed click chemistry inside living cells.

Methods in enzymology·2026

Same journal

Site-specific antibody labeling via endo-S2 mediated Fc glycan remodeling.

Methods in enzymology·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 25, 2026

Open Source High Content Analysis Utilizing Automated Fluorescence Lifetime Imaging Microscopy

Open Source High Content Analysis Utilizing Automated Fluorescence Lifetime Imaging Microscopy

Published on: January 18, 2017

Open source tools for fluorescent imaging.

Nicholas A Hamilton¹

¹Division of Genomics Computational Biology, Institute for Molecular Bioscience, The University of Queensland, St. Lucia, Brisbane, Queensland, Australia.

Methods in Enzymology

|January 24, 2012

Summary

This summary is machine-generated.

Open source bio-image analysis tools are crucial for automated fluorescent microscopy. These high-quality, interconnected projects offer a viable, verifiable alternative to commercial solutions, enhancing research throughput and data extraction.

More Related Videos

Light Sheet-based Fluorescence Microscopy of Living or Fixed and Stained Tribolium castaneum Embryos

Light Sheet-based Fluorescence Microscopy of Living or Fixed and Stained Tribolium castaneum Embryos

Published on: April 28, 2017

Fluorescence Lifetime Macro Imager for Biomedical Applications

Fluorescence Lifetime Macro Imager for Biomedical Applications

Published on: April 7, 2023

Related Experiment Videos

Last Updated: May 25, 2026

Open Source High Content Analysis Utilizing Automated Fluorescence Lifetime Imaging Microscopy

Open Source High Content Analysis Utilizing Automated Fluorescence Lifetime Imaging Microscopy

Published on: January 18, 2017

Light Sheet-based Fluorescence Microscopy of Living or Fixed and Stained Tribolium castaneum Embryos

Light Sheet-based Fluorescence Microscopy of Living or Fixed and Stained Tribolium castaneum Embryos

Published on: April 28, 2017

Fluorescence Lifetime Macro Imager for Biomedical Applications

Fluorescence Lifetime Macro Imager for Biomedical Applications

Published on: April 7, 2023

Area of Science:

Biotechnology
Microscopy
Image Analysis

Background:

Microscopy automation and increased imaging dimensions necessitate advanced quantitative analysis tools.
Existing bio-image analysis tools face challenges in throughput and full information extraction.

Purpose of the Study:

To provide an overview of the current state of open source software for fluorescent microscopy analysis.
To highlight the capabilities, features, and benefits of open source bio-image analysis projects.
To advocate for the use and development of open source methods in scientific research.

Main Methods:

Review and description of major open source bio-image analysis projects.
Analysis of project capabilities, features, and user bases.
Discussion of the interoperability and interconnectedness of these tools.

Main Results:

Numerous high-quality, well-supported open source bio-image analysis projects are available.
These projects cover all aspects of image analysis, from capture to publication.
Open source solutions offer a viable and verifiable alternative to commercial software.

Conclusions:

Open source bio-image analysis software is essential for modern microscopy.
These tools foster collaboration and knowledge verification through shared methods and data.
Adoption of open source solutions accelerates scientific discovery and reproducibility.