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

Genome-wide characterization of the Bcl-2-associated athanogene (BAG) gene family and functional analysis of ZmBAG14 under drought stress in maize.

Plant physiology and biochemistry : PPB·2026
Same author

Reconfigurable Photoelectric Coaxial Fiber-Based Memristors for Neuromorphic Computing.

ACS nano·2026
Same author

Pharmacokinetic characteristics of Bletilla Striata active components in rats and <sup>1</sup>H NMR metabolomics study on ulcerative colitis.

Fitoterapia·2026
Same author

Corrigendum to "Peroxisome proliferator-activated receptor gamma (PPARγ)-targeted Gel/Mg/Lip@Gigantol nanoplatform attenuates skin barrier disruption-associated aging in mice via NLRP3 suppression" [2025Sep5;328(Pt1):147464.doi:10.1016/j.ijbiomac.2025.147464].

International journal of biological macromolecules·2026
Same author

Benzophenone-2 disrupts craniofacial cartilage development via esr2a-Dependent inhibition of endothelin signaling in zebrafish larvae.

Environmental research·2026
Same author

Two-Dimensional Covalent Organic Framework Membranes: Multi-Scale Design and Forward-Looking Perspectives.

Advanced materials (Deerfield Beach, Fla.)·2026

Related Experiment Video

Updated: Sep 11, 2025

Sample Drift Correction Following 4D Confocal Time-lapse Imaging
10:04

Sample Drift Correction Following 4D Confocal Time-lapse Imaging

Published on: April 12, 2014

16.5K

Motion Artifact Correction in Deep-Tissue Three-Photon Fluorescence Microscopy Using Adaptive Optical Flow Learning

Yifei Li1, Runnan Zhang2, Keying Li3

  • 1State Key Laboratory of Extreme Photonics and Instrumentation, Centre for Optical and Electromagnetic Research, College of Optical Science and Engineering, International Research Center for Advanced Photonics, Zhejiang University, Hangzhou, China.

Journal of Biophotonics
|August 17, 2025
PubMed
Summary

Motion artifacts in deep tissue imaging are corrected by StabiFormer, a novel transformer network. This computational solution enables clear 3D visualization of dynamic biological systems, advancing physiological research.

Keywords:
intravital imagingmotion artifact correctionoptical flow learningthree‐photon fluorescence microscopytransformer network

More Related Videos

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
Human Fetal Blood Flow Quantification with Magnetic Resonance Imaging and Motion Compensation
06:56

Human Fetal Blood Flow Quantification with Magnetic Resonance Imaging and Motion Compensation

Published on: January 7, 2021

2.5K

Related Experiment Videos

Last Updated: Sep 11, 2025

Sample Drift Correction Following 4D Confocal Time-lapse Imaging
10:04

Sample Drift Correction Following 4D Confocal Time-lapse Imaging

Published on: April 12, 2014

16.5K
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
Human Fetal Blood Flow Quantification with Magnetic Resonance Imaging and Motion Compensation
06:56

Human Fetal Blood Flow Quantification with Magnetic Resonance Imaging and Motion Compensation

Published on: January 7, 2021

2.5K

Area of Science:

  • Biomedical Optics
  • Computational Imaging
  • Neuroscience

Background:

  • Three-photon fluorescence microscopy (3PFM) provides high-resolution deep tissue imaging but suffers from motion artifacts.
  • Existing motion correction methods are insufficient for intense, non-uniform motion in low-texture or deformed biological samples.

Purpose of the Study:

  • To develop a robust computational method for correcting motion artifacts in 3PFM.
  • To enable artifact-free volumetric imaging in dynamic physiological environments.

Main Methods:

  • Introduced StabiFormer, a transformer-based optical flow learning network.
  • Developed a stable-dynamic feature extractor to capture interlayer dynamics for accurate image registration.

Main Results:

  • StabiFormer achieved near-zero displacement error in brain vasculature imaging.
  • Enabled artifact-free 3D visualization of intestinal macrophages and vasculature at 300 μm depth.
  • Demonstrated robust performance on cerebrovascular and intestinal 3PFM datasets.

Conclusions:

  • StabiFormer offers a noninvasive computational solution for motion-artifact-free volumetric imaging.
  • Facilitates quantitative investigations in dynamic organ systems previously limited by motion artifacts.