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

You might also read

Related Articles

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

Sort by
Same author

High-fidelity fast fluorescence lifetime imaging by event-based denoising.

Nature biotechnology·2026
Same author

High numerical aperture confocal volumetric mesoscope reveals mesoscale subcellular dynamics in vivo.

Nature biotechnology·2026
Same author

Development and validation of an event-specific detection method for WYN029GmA soybean based on TaqMan qPCR.

Frontiers in plant science·2026
Same author

Real-time robust autofocus method enabling sustained intravital scanning light field imaging.

Nature communications·2026
Same author

A multi-modal foundation model for brain disease diagnosis and medical imaging.

Patterns (New York, N.Y.)·2026
Same author

Isolation, identification and pathogenicity analysis of a virulent duck enteritis virus strain causing outbreak in vaccinated duck flocks.

Poultry science·2026

Related Experiment Video

Updated: Sep 6, 2025

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

7.0K

Imaging Dynamics Beneath Turbid Media via Parallelized Single-Photon Detection.

Shiqi Xu1, Xi Yang1, Wenhui Liu1,2

  • 1Department of Biomedical Engineering, Duke University, Durham, NC, 27708, USA.

Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|June 24, 2022
PubMed
Summary

This study uses a novel deep neural network and single-photon camera to reconstruct deep-tissue scattering dynamics. The method enables real-time video imaging of dynamic events beneath scattering tissues, advancing noninvasive optical imaging.

Keywords:
deep imagingdynamic scatteringsingle-photon avalanche diode array

More Related Videos

Direct Imaging of Laser-driven Ultrafast Molecular Rotation
10:52

Direct Imaging of Laser-driven Ultrafast Molecular Rotation

Published on: February 4, 2017

9.8K
Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy ATOM
07:19

Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy ATOM

Published on: June 28, 2017

10.4K

Related Experiment Videos

Last Updated: Sep 6, 2025

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

7.0K
Direct Imaging of Laser-driven Ultrafast Molecular Rotation
10:52

Direct Imaging of Laser-driven Ultrafast Molecular Rotation

Published on: February 4, 2017

9.8K
Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy ATOM
07:19

Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy ATOM

Published on: June 28, 2017

10.4K

Area of Science:

  • Biomedical Optics
  • Medical Imaging
  • Photonics

Background:

  • Noninvasive optical imaging in dynamic scattering media is crucial for biomedical applications but technically challenging.
  • Traditional methods focus on absorption or fluorescence, overlooking temporal correlation of scattered light.
  • Few studies have experimentally utilized temporal correlation data for deep-tissue imaging.

Purpose of the Study:

  • To demonstrate deep-tissue video reconstruction of decorrelation dynamics using temporal correlation data.
  • To develop a method for imaging dynamic events beneath scattering tissues.
  • To assess the capability of the developed model for monitoring flow dynamics.

Main Methods:

  • Utilized a single-photon avalanche diode array camera to monitor temporal dynamics of speckle fluctuations.
  • Employed a customized fiber bundle array to capture data from multiple tissue surface locations.
  • Applied a deep neural network to process single-photon measurements for video reconstruction.

Main Results:

  • Successfully reconstructed videos of scattering dynamics beneath decorrelating tissue phantoms.
  • Demonstrated imaging of transient dynamic events up to 8 mm deep with millimeter resolution.
  • Showcased the model's flexibility in monitoring flow speed within buried phantom vessels.

Conclusions:

  • The developed deep neural network approach enables effective deep-tissue video reconstruction of scattering dynamics.
  • This technique offers a promising advancement for noninvasive biomedical optical imaging.
  • The model shows potential for quantitative assessment of dynamic processes in biological tissues.