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

Spatial Transcriptomic Atlas Reveals That Forkhead Box O3-Mediated Mitochondrial Dynamics Imbalance Drives Premature Ovarian Insufficiency in Mice.

Aging cell·2026
Same author

APASL clinical practice guidance: the diagnosis and management of patients with Wilson's disease.

Hepatology international·2026
Same author

Prediction of Coal Spontaneous Combustion Risk under Poor Oxygen Concentration Based on Fuzzy Clustering and Lattice Tightness.

ACS omega·2026
Same author

Multi-omics analysis identifies key genes and functional loci affecting teat number in American Large White and Landrace pigs and their application in optimizing genomic selection models.

BMC genomics·2026
Same author

A TaMYB2-TaMAP3K17 module enhances drought tolerance by promoting reactive oxygen species scavenging in wheat.

aBIOTECH·2026
Same author

Correction: Benchmark evaluation of video large language models in quality assessment of science popularization videos for dry eye.

Scientific reports·2026

Related Experiment Video

Updated: Nov 5, 2025

In vivo Structural Assessments of Ocular Disease in Rodent Models using Optical Coherence Tomography
07:44

In vivo Structural Assessments of Ocular Disease in Rodent Models using Optical Coherence Tomography

Published on: July 24, 2020

3.1K

Computational Model-Based Estimation of Mouse Eyeball Structure From Two-Dimensional Flatmount Microscopy Images.

Hongxiao Li1,2, Hanyi Yu3, Yong-Kyu Kim4

  • 1Department of Mathematics and Statistics, Georgia State University, Atlanta, GA, USA.

Translational Vision Science & Technology
|May 18, 2021
PubMed
Summary

A new method reconstructs 3D eyeball structure from 2D images, improving retinal pigment epithelial (RPE) cell analysis. This technique enhances RPE morphometry and aids in diagnosing eye diseases.

More Related Videos

A Custom Multiphoton Microscopy Platform for Live Imaging of Mouse Cornea and Conjunctiva
06:53

A Custom Multiphoton Microscopy Platform for Live Imaging of Mouse Cornea and Conjunctiva

Published on: May 17, 2020

5.6K
Video-oculography in Mice
09:43

Video-oculography in Mice

Published on: July 19, 2012

24.1K

Related Experiment Videos

Last Updated: Nov 5, 2025

In vivo Structural Assessments of Ocular Disease in Rodent Models using Optical Coherence Tomography
07:44

In vivo Structural Assessments of Ocular Disease in Rodent Models using Optical Coherence Tomography

Published on: July 24, 2020

3.1K
A Custom Multiphoton Microscopy Platform for Live Imaging of Mouse Cornea and Conjunctiva
06:53

A Custom Multiphoton Microscopy Platform for Live Imaging of Mouse Cornea and Conjunctiva

Published on: May 17, 2020

5.6K
Video-oculography in Mice
09:43

Video-oculography in Mice

Published on: July 19, 2012

24.1K

Area of Science:

  • Ophthalmology
  • Cell Biology
  • Biomedical Imaging

Background:

  • Retinal pigment epithelial (RPE) cells are crucial for photoreceptor support and protection.
  • Understanding RPE cell morphology, organization, and growth is vital for eye research and disease diagnosis.
  • Current methods face challenges in analyzing RPE cells within the intact eyeball structure.

Purpose of the Study:

  • To develop a novel method for estimating the 3D eyeball sphere from 2D tissue flatmount microscopy images.
  • To enable detailed RPE morphometry analysis on the authentic 3D eyeball surface.
  • To facilitate research into RPE cell functions and eye disease mechanisms.

Main Methods:

  • A 3D reconstruction model was developed to estimate eyeball geometry from 2D microscopy images.
  • An error-correction term was formulated to account for tissue distortions during sample preparation.
  • Ground truth eyeball diameters were precisely measured using noncontact light-emitting diode micrometry for model validation.

Main Results:

  • The error-correction model significantly improved the accuracy of eyeball diameter estimation.
  • Average relative error in diameter estimation decreased from 14% to 5%.
  • Absolute error in diameter estimation was reduced from 0.22 mm to 0.03 mm.

Conclusions:

  • A validated method for 3D RPE morphometry analysis on the eyeball sphere was established.
  • This technique is essential for advancing RPE research and improving eye disease diagnosis.
  • The method supports the characterization of eyeball volume growth in diseased conditions.