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

Confocal Fluorescence Microscopy01:16

Confocal Fluorescence Microscopy

19.5K
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,...
19.5K
Super-resolution Fluorescence Microscopy01:37

Super-resolution Fluorescence Microscopy

12.0K
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...
12.0K
Three-Dimensional Microscopy in Microbiology01:28

Three-Dimensional Microscopy in Microbiology

651
Three-dimensional imaging techniques are essential in cell biology, allowing researchers to visualize intricate cellular structures with high resolution. Two prominent methods, Differential Interference Contrast Microscopy (DIC) and Confocal Scanning Laser Microscopy (CSLM), provide distinct advantages for imaging live and thick specimens, respectively.Differential Interference Contrast MicroscopyDIC microscopy enhances contrast in transparent, unstained samples by converting phase...
651
Imaging Biological Samples with Optical Microscopy01:18

Imaging Biological Samples with Optical Microscopy

8.4K
Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...
8.4K

You might also read

Related Articles

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

Sort by
Same author

Crystalline lens geometry from a clinical OCT-based biometer in pre-cataract surgery patients.

Research square·2026
Same author

LG-Sleep: Local and Global Temporal Dependencies for Mice Sleep Scoring.

IEEE sensors letters·2025
Same author

Sparse Optoacoustic Sensing With Convolutional Dictionary Learning.

IEEE transactions on bio-medical engineering·2025
Same author

Postoperative intraocular lens tilt from preoperative full crystalline lens geometry using machine learning.

Biomedical optics express·2025
Same author

Robust EEG-based Emotion Recognition Using an Inception and Two-sided Perturbation Model.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same author

Integrating Learning-Based Priors With Physics-Based Models in Ultrasound Elasticity Reconstruction.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control·2024
Same journal

Analysis of End-Tidal CO2 Variability During Plateau Waves Episodes: An Information Theoretic Approach<sup></sup>.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

AI and Tomosynthesis for Breast Cancer Molecular Subtyping: A step toward precision medicine<sup></sup>.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

Towards Sustainable Protein Recovery from Biological Waste: Assessing Polyethersulfone-based Microfiltration.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

Analysis of the cardiovascular response to standardized polymicrobial peritonitis experimental model.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

Automated Wrist Ultrasound Image Bone Enhancement and Segmentation Using Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

A Deep Learning approach for Depressive Symptoms assessment in Parkinson's disease patients using facial videos.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
See all related articles

Related Experiment Video

Updated: Dec 6, 2025

A Guide to Structured Illumination TIRF Microscopy at High Speed with Multiple Colors
11:15

A Guide to Structured Illumination TIRF Microscopy at High Speed with Multiple Colors

Published on: May 30, 2016

25.8K

Compressed Sensing Structured Illumination Microscopy.

Baturay Ozgurun, Mujdat Cetin

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |October 6, 2020
    PubMed
    Summary
    This summary is machine-generated.

    We introduce a novel compressed sensing (CS) framework for super-resolution structured illumination microscopy (SR-SIM). This method reduces readout time and photobleaching by simultaneously sampling and down-modulating the object scene.

    More Related Videos

    Lensless Fluorescent Microscopy on a Chip
    11:23

    Lensless Fluorescent Microscopy on a Chip

    Published on: August 17, 2011

    18.0K
    Single Molecule Fluorescence Microscopy on Planar Supported Bilayers
    20:00

    Single Molecule Fluorescence Microscopy on Planar Supported Bilayers

    Published on: October 31, 2015

    14.2K

    Related Experiment Videos

    Last Updated: Dec 6, 2025

    A Guide to Structured Illumination TIRF Microscopy at High Speed with Multiple Colors
    11:15

    A Guide to Structured Illumination TIRF Microscopy at High Speed with Multiple Colors

    Published on: May 30, 2016

    25.8K
    Lensless Fluorescent Microscopy on a Chip
    11:23

    Lensless Fluorescent Microscopy on a Chip

    Published on: August 17, 2011

    18.0K
    Single Molecule Fluorescence Microscopy on Planar Supported Bilayers
    20:00

    Single Molecule Fluorescence Microscopy on Planar Supported Bilayers

    Published on: October 31, 2015

    14.2K

    Area of Science:

    • Microscopy
    • Optical Imaging
    • Biophysics

    Background:

    • Super-resolution structured illumination microscopy (SR-SIM) faces challenges with long acquisition times and photobleaching.
    • Compressed sensing (CS) offers potential solutions by reducing measurement requirements and excitation light intensity.

    Purpose of the Study:

    • To develop a new SR-SIM framework leveraging compressed sensing (CS).
    • To address limitations of conventional SR-SIM, specifically long readout times and photobleaching.

    Main Methods:

    • A novel framework integrating compressed sensing (CS) with SR-SIM is proposed.
    • The core innovation involves simultaneous sampling and down-modulation of the object scene.
    • The method aims to reduce the number of required measurements and excitation light exposure.

    Main Results:

    • Simulation-based experiments with computer-generated super-resolution microscopy images were conducted.
    • The framework's performance was evaluated under conditions of reduced data quality and quantity.
    • The proposed method demonstrated potential for faster imaging and reduced photobleaching.

    Conclusions:

    • The developed CS-based SR-SIM framework effectively addresses key limitations of traditional SR-SIM.
    • Simultaneous sampling and down-modulation represent a significant advancement in SR-SIM methodology.
    • This approach holds promise for improved efficiency and reduced photodamage in super-resolution imaging.