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...

Confocal Fluorescence Microscopy

Confocal Fluorescence Microscopy

Confocal microscopy is an advanced microscopic technique. The prime advantage of the confocal microscope over other microscopy techniques is its ability to block the out-of-focus light from the illuminated samples using pinholes. It is widely used with fluorescence optics to obtain high-resolution, sharp contrast images. Unlike optical microscopes, confocal microscopes use a focused beam of light laser to scan the entire sample surface at different z-planes. These microscopes are, therefore,...

You might also read

Related Articles

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

Sort by

Same author

Design and validation of a perfusion bioreactor for long-term human bone explant culture.

JBMR plus·2026

Same author

U<b>se of benzodiazepines and medications for opioid use disorder for withdrawal management in a hospital-based setting for individuals exposed to benzodiazepine-contaminated fentanyl: A case serie</b>s.

Drug and alcohol dependence reports·2026

Same author

Transmigrated neutrophils on the ocular surface and in other tissues: A narrative review.

The ocular surface·2026

Same author

Point-of-care ultrasound in Canadian anesthesiology residency programs: a follow-up survey.

Canadian journal of anaesthesia = Journal canadien d'anesthesie·2026

Same author

Phenotype of Tear Leukocytes in Seasonal Ocular Allergy and Their Potential Impacts on Ocular Surface Inflammation.

Ocular immunology and inflammation·2026

Same author

Physically Informed 3D Food Reconstruction: Methods and Results.

IEEE journal of biomedical and health informatics·2026

Same journal

Turbulent flow in a vortex separator with a directed pipe inlet.

Scientific reports·2026

Same journal

Systematic characteristic evaluation of clay-based cementitious material derived from calcium carbide residue and waste tile powder.

Scientific reports·2026

Same journal

Retraction Note: Improvement of a rapid diagnostic application of monoclonal antibodies against avian influenza H7 subtype virus using Europium nanoparticles.

Scientific reports·2026

Same journal

Applying large language models to spam detection in the Kazakh low-resource language setting.

Scientific reports·2026

Same journal

An open-source 3D printing system enabling in-situ freeze-thaw processing of hydrogels.

Scientific reports·2026

Same journal

An enhanced EfficientNet framework for automated waste classification using cosine annealing and label smoothing.

Scientific reports·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Apr 11, 2026

Live Images of GLUT4 Protein Trafficking in Mouse Primary Hypothalamic Neurons Using Deconvolution Microscopy

Live Images of GLUT4 Protein Trafficking in Mouse Primary Hypothalamic Neurons Using Deconvolution Microscopy

Published on: December 7, 2017

Bayesian-based deconvolution fluorescence microscopy using dynamically updated nonstationary expectation estimates.

Alexander Wong¹, Xiao Yu Wang¹, Maud Gorbet¹

¹Department of Systems Design Engineering, University of Waterloo, Ontario, Canada, N2L 3G1.

Scientific Reports

|June 9, 2015

Summary

This summary is machine-generated.

This study introduces a new Bayesian deconvolution method for fluorescence microscopy. It enhances image quality in noisy, low signal-to-noise ratio conditions without needing spatial regularization.

More Related Videos

Lensless Fluorescent Microscopy on a Chip

Lensless Fluorescent Microscopy on a Chip

Published on: August 17, 2011

Author Spotlight: Enhanced Multiplex Immunofluorescent Microscopy Protocol for Neuroscience Research

Author Spotlight: Enhanced Multiplex Immunofluorescent Microscopy Protocol for Neuroscience Research

Published on: June 21, 2024

Related Experiment Videos

Last Updated: Apr 11, 2026

Live Images of GLUT4 Protein Trafficking in Mouse Primary Hypothalamic Neurons Using Deconvolution Microscopy

Live Images of GLUT4 Protein Trafficking in Mouse Primary Hypothalamic Neurons Using Deconvolution Microscopy

Published on: December 7, 2017

Lensless Fluorescent Microscopy on a Chip

Lensless Fluorescent Microscopy on a Chip

Published on: August 17, 2011

Author Spotlight: Enhanced Multiplex Immunofluorescent Microscopy Protocol for Neuroscience Research

Author Spotlight: Enhanced Multiplex Immunofluorescent Microscopy Protocol for Neuroscience Research

Published on: June 21, 2024

Area of Science:

Microscopy
Image Processing
Computational Biology

Background:

Fluorescence microscopy is crucial for biological studies.
Image deconvolution enhances resolution and contrast.
Bayesian methods are popular for deconvolution but struggle with noise.

Purpose of the Study:

To present a novel Bayesian deconvolution method.
To address challenges of noise in low SNR fluorescence microscopy images.
To improve fluorescence image quality without spatial regularization.

Main Methods:

Developed a Bayesian-based deconvolution technique.
Incorporated dynamically updated nonstationary expectation estimates.
Applied the method to fluorescence microscopy data.

Main Results:

The method effectively improves fluorescence microscopy image quality.
Enhanced performance was observed under noisy, low SNR conditions.
No explicit spatial regularization was required for improvement.

Conclusions:

The proposed Bayesian method offers a robust solution for deconvolution in challenging imaging scenarios.
This technique advances fluorescence microscopy image analysis by effectively handling noise.
The method provides a valuable tool for researchers studying biological specimens with low signal-to-noise ratios.