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

7.0K
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...
7.0K
Confocal Fluorescence Microscopy01:16

Confocal Fluorescence Microscopy

13.3K
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,...
13.3K

You might also read

Related Articles

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

Sort by
Same author

Uni-portal thoracoscopic lymph node dissection under the left prominence: pause ventilation technique.

Journal of cardiothoracic surgery·2026
Same author

Clinical study on the therapeutic effect of large-area cupping therapy for lumbar disc herniation of cold-damp type (a Traditional Chinese Medicine syndrome).

Frontiers in medicine·2026
Same author

Bakuchiol, a potentially toxic component in Fructus psoraleae, causes liver damage in vitro by affecting the homeostasis of the liver GABA signalling system.

Journal of ethnopharmacology·2026
Same author

Rosmarinic acid-derived micelles potentiated dextran hydrogel for concurrent mechanical reinforcement and inflammatory microenvironment remodeling in chronic diabetic wound healing.

Carbohydrate polymers·2026
Same author

Isolation and characterization of a highly pathogenic Orthoflavivirus associated with ascites syndrome in Chinese soft-shelled turtles (Pelodiscus sinensis).

Archives of virology·2026
Same author

A Personalized FSH Dosing Strategy for Women with Polycystic Ovary Syndrome Undergoing GnRH Antagonist Protocols.

Biomedicines·2026

Related Experiment Video

Updated: Jul 6, 2025

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
11:34

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

Published on: December 3, 2013

15.7K

Fast digital refocusing Fourier ptychographic microscopy method based on convolutional neural network.

Mingdi Liu, Ruofei Wu, Zicong Luo

    Optics Express
    |January 4, 2024
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a new convolutional neural network to improve Fourier ptychographic microscopy (FPM) image quality by accurately predicting defocus distances. This method enhances imaging depth-of-field and maintains high accuracy across diverse biological samples.

    More Related Videos

    Registration of Calcium Transients in Mouse Neuromuscular Junction with High Temporal Resolution using Confocal Microscopy
    11:12

    Registration of Calcium Transients in Mouse Neuromuscular Junction with High Temporal Resolution using Confocal Microscopy

    Published on: December 1, 2021

    2.0K
    Lensless Fluorescent Microscopy on a Chip
    11:23

    Lensless Fluorescent Microscopy on a Chip

    Published on: August 17, 2011

    17.7K

    Related Experiment Videos

    Last Updated: Jul 6, 2025

    High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
    11:34

    High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

    Published on: December 3, 2013

    15.7K
    Registration of Calcium Transients in Mouse Neuromuscular Junction with High Temporal Resolution using Confocal Microscopy
    11:12

    Registration of Calcium Transients in Mouse Neuromuscular Junction with High Temporal Resolution using Confocal Microscopy

    Published on: December 1, 2021

    2.0K
    Lensless Fluorescent Microscopy on a Chip
    11:23

    Lensless Fluorescent Microscopy on a Chip

    Published on: August 17, 2011

    17.7K

    Area of Science:

    • Microscopy
    • Computational Imaging
    • Biomedical Optics

    Background:

    • Fourier ptychographic microscopy (FPM) offers high resolution and large field-of-view imaging.
    • Traditional FPM reconstruction struggles with out-of-focus artifacts, degrading image quality.
    • Accurate defocus estimation is crucial for robust FPM image reconstruction.

    Purpose of the Study:

    • To develop a novel method for accurate defocus-distance estimation in FPM.
    • To improve the image quality and extend the imaging depth-of-field of FPM systems.
    • To address the limitations of traditional FPM reconstruction in the presence of defocus.

    Main Methods:

    • A defocus-distance regression network utilizing convolutional neural networks (CNNs) was designed.
    • The network was trained and validated using experimental FPM data.
    • Quantitative evaluation involved calculating the root-mean-square error (RMSE) between predicted and true defocus distances.

    Main Results:

    • The proposed CNN-based method achieved a low RMSE of approximately 6.2 µm for defocus distance prediction.
    • The method demonstrated strong generalization capabilities across different biological samples.
    • The effective imaging depth-of-field of the FPM system was extended by over a factor of 3.

    Conclusions:

    • The developed defocus-distance regression network significantly enhances FPM image reconstruction quality.
    • This approach provides a robust solution for handling out-of-focus issues in FPM.
    • The method offers improved imaging performance and extended depth-of-field for biological sample analysis.