Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Super-resolution Fluorescence Microscopy01:37

Super-resolution Fluorescence Microscopy

14.8K
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...
14.8K

You might also read

Related Articles

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

Sort by
Same author

ACE-RT, A Cloud-Based Tool for Remote Radiotherapy Contouring Support in Lower-Resourced Settings: A Pilot Evaluation.

Clinical oncology (Royal College of Radiologists (Great Britain))·2025
Same author

A qualitative analysis of health information-sharing networks in the Indonesian poultry sector.

Preventive veterinary medicine·2023
Same author

Oral mucosal melanoma in situ: a case report and review of the literature.

International journal of oral and maxillofacial surgery·2023
Same author

Happy to be extracted.

British dental journal·2022
Same author

Hyperuricaemia, gout and allopurinol in the CKD Queensland registry.

Journal of nephrology·2021
Same author

Extracranial dose and the risk of radiation-induced malignancy after intracranial stereotactic radiosurgery: is it time to establish a therapeutic reference level?

Acta neurochirurgica·2020
Same journal

Serum vitamin D level and its association with vertigo frequency and severity in Meniere disease.

Scientific reports·2026
Same journal

PFA-Net: a physics-informed feature enhancement and attention network for interpretable bearing fault diagnosis under strong noise.

Scientific reports·2026
Same journal

Circulating inflammatory, redox, and apoptosis-related alterations in drug-naive idiopathic pulmonary fibrosis: an exploratory case-control study.

Scientific reports·2026
Same journal

A baseline-oriented dynamic aggregation approach for demand-side heterogeneous controllable resources.

Scientific reports·2026
Same journal

Temporal precision and accuracy in schizophrenia: an exploratory study.

Scientific reports·2026
Same journal

Prefrontal EEG spectral and nonlinear signatures of subthreshold depression during resting state and affectively valenced picture/video viewing: a participant-level analysis.

Scientific reports·2026
See all related articles

Related Experiment Video

Updated: Mar 25, 2026

High-Throughput Total Internal Reflection Fluorescence and Direct Stochastic Optical Reconstruction Microscopy Using a Photonic Chip
14:09

High-Throughput Total Internal Reflection Fluorescence and Direct Stochastic Optical Reconstruction Microscopy Using a Photonic Chip

Published on: November 16, 2019

7.5K

Fluorescence microscopy image noise reduction using a stochastically-connected random field model.

S A Haider1, A Cameron1, P Siva1

  • 1Vision and Image Processing (VIP) Research Group, Department of Systems Design Engineering, University of Waterloo, 200 University Avenue W, Waterloo, ON, N2L 3G1, Canada.

Scientific Reports
|February 18, 2016
PubMed
Summary
This summary is machine-generated.

This study presents a new method using stochastically-connected random fields (SRF) to reduce noise in fluorescence microscopy images. The SRF approach effectively enhances image quality while preserving crucial cellular details.

More Related Videos

Author Spotlight: Enhanced Multiplex Immunofluorescent Microscopy Protocol for Neuroscience Research
05:22

Author Spotlight: Enhanced Multiplex Immunofluorescent Microscopy Protocol for Neuroscience Research

Published on: June 21, 2024

911
Continuous Measurement of Biological Noise in Escherichia Coli Using Time-lapse Microscopy
08:25

Continuous Measurement of Biological Noise in Escherichia Coli Using Time-lapse Microscopy

Published on: April 27, 2021

4.2K

Related Experiment Videos

Last Updated: Mar 25, 2026

High-Throughput Total Internal Reflection Fluorescence and Direct Stochastic Optical Reconstruction Microscopy Using a Photonic Chip
14:09

High-Throughput Total Internal Reflection Fluorescence and Direct Stochastic Optical Reconstruction Microscopy Using a Photonic Chip

Published on: November 16, 2019

7.5K
Author Spotlight: Enhanced Multiplex Immunofluorescent Microscopy Protocol for Neuroscience Research
05:22

Author Spotlight: Enhanced Multiplex Immunofluorescent Microscopy Protocol for Neuroscience Research

Published on: June 21, 2024

911
Continuous Measurement of Biological Noise in Escherichia Coli Using Time-lapse Microscopy
08:25

Continuous Measurement of Biological Noise in Escherichia Coli Using Time-lapse Microscopy

Published on: April 27, 2021

4.2K

Area of Science:

  • Biology
  • Image Processing
  • Computational Science

Background:

  • Fluorescence microscopy is vital for biological research, enabling analysis of cellular components and processes.
  • Image noise is a significant challenge, hindering accurate interpretation of fluorescence microscopy data.
  • Existing noise reduction methods often struggle to preserve fine cellular structures.

Purpose of the Study:

  • To introduce a novel noise reduction technique for fluorescence microscopy images.
  • To address the limitations of current methods in preserving image details.
  • To improve the signal-to-noise ratio and contrast in biological imaging.

Main Methods:

  • Formulating noise reduction as a Maximum A Posteriori estimation problem.
  • Developing and applying a novel stochastically-connected random field (SRF) model.
  • Combining principles from random graph and field theory within the SRF model.
  • Validating the approach using both synthetic and real fluorescence microscopy data.

Main Results:

  • The SRF method demonstrated superior noise reduction compared to existing algorithms.
  • Quantitative metrics showed significant improvements in signal-to-noise ratio (SNR) for synthetic data.
  • Real microscopy data analysis confirmed high SNR and contrast-to-noise ratio (CNR) with the SRF approach.
  • The method successfully preserved cellular structures and subtle details while reducing noise.

Conclusions:

  • The stochastically-connected random field (SRF) model offers a powerful new tool for noise reduction in fluorescence microscopy.
  • SRF effectively balances noise suppression with the preservation of critical biological information.
  • This technique has the potential to significantly advance biological imaging and analysis.