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

Glaucoma: Overview01:25

Glaucoma: Overview

1.2K
Glaucoma is an eye condition characterized by increased intraocular pressure that damages the retina and optic nerve, leading to irreversible blindness if left untreated. The human eye has various components, including the cornea, iris, pupil, lens, and optic nerve. Aqueous humor is secreted by the epithelium of the ciliary body in the posterior chamber and flows through the trabecular meshwork and canal of Schlemm, maintaining normal intraocular pressure. The trabecular meshwork and the canal...
1.2K
Open Angle Glaucoma: Treatment01:27

Open Angle Glaucoma: Treatment

908
In open-angle glaucoma, the iridocorneal angle remains open, but the trabecular meshwork becomes stiff, slowing down the outflow of aqueous humor. This causes a buildup of aqueous humor in the anterior chamber, leading to a sudden increase in intraocular pressure. The treatment for open-angle glaucoma focuses on reducing the elevated intraocular pressure by either decreasing the secretion of aqueous humor or increasing its outflow.
Drugs such as carbonic anhydrase inhibitors, α2- and...
908
Angle Closure Glaucoma: Treatment01:28

Angle Closure Glaucoma: Treatment

1.1K
Angle-closure glaucoma, or closed-angle glaucoma, is an eye condition where the iris bulges out and blocks the iridocorneal angle, resulting in a buildup of aqueous humor and increased intraocular pressure. Immediate medical attention is necessary due to the sudden onset of symptoms. The treatment for angle-closure glaucoma includes short-term and long-term approaches. Short-term treatment involves using eye drops like pilocarpine to lower intraocular pressure by increasing aqueous humor...
1.1K
Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

1.7K
Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
1.7K

You might also read

Related Articles

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

Sort by
Same author

Data Volume and the Need for Clinical Decision Support in Glaucoma Care.

Ophthalmology science·2026
Same author

Extraction of Glaucoma Diagnosis, Type, and Severity from Clinical Notes using Secure Cloud-based Large Language Models.

medRxiv : the preprint server for health sciences·2026
Same author

GLLaucoMed: A Secure LLM-Powered Agentic Workflow for Automated Medication Extraction from Free-Text Glaucoma Clinical Notes.

medRxiv : the preprint server for health sciences·2026
Same author

Optic Disc Fundus Images Retain Biometric Identity Signals Under Deep Learning.

Research square·2026
Same author

Design and Validation of an AI-Assisted Sequential Screening Framework for Psychological Distress in Glaucoma.

medRxiv : the preprint server for health sciences·2026
Same author

Development and Pilot Testing of a Mobile App Psychosocial Intervention for Psychological Distress in Individuals with Glaucoma.

medRxiv : the preprint server for health sciences·2026

Related Experiment Video

Updated: Jan 2, 2026

Assessing Early Stage Open-Angle Glaucoma in Patients by Isolated-Check Visual Evoked Potential
07:11

Assessing Early Stage Open-Angle Glaucoma in Patients by Isolated-Check Visual Evoked Potential

Published on: May 25, 2020

6.7K

Estimating Rates of Progression and Predicting Future Visual Fields in Glaucoma Using a Deep Variational Autoencoder.

Samuel I Berchuck1,2, Sayan Mukherjee3, Felipe A Medeiros4

  • 1Duke Eye Center and Department of Ophthalmology, Duke University, Durham, North Carolina, USA.

Scientific Reports
|December 4, 2019
PubMed
Summary

A deep learning algorithm using a variational auto-encoder (VAE) significantly improves the detection of glaucoma progression and prediction of future visual field loss compared to traditional methods. This advanced technique offers better accuracy in assessing disease trajectory.

More Related Videos

Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping
07:11

Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping

Published on: December 8, 2023

2.2K
Assessing Binocular Central Visual Field and Binocular Eye Movements in a Dichoptic Viewing Condition
07:45

Assessing Binocular Central Visual Field and Binocular Eye Movements in a Dichoptic Viewing Condition

Published on: July 21, 2020

4.9K

Related Experiment Videos

Last Updated: Jan 2, 2026

Assessing Early Stage Open-Angle Glaucoma in Patients by Isolated-Check Visual Evoked Potential
07:11

Assessing Early Stage Open-Angle Glaucoma in Patients by Isolated-Check Visual Evoked Potential

Published on: May 25, 2020

6.7K
Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping
07:11

Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping

Published on: December 8, 2023

2.2K
Assessing Binocular Central Visual Field and Binocular Eye Movements in a Dichoptic Viewing Condition
07:45

Assessing Binocular Central Visual Field and Binocular Eye Movements in a Dichoptic Viewing Condition

Published on: July 21, 2020

4.9K

Area of Science:

  • Ophthalmology
  • Artificial Intelligence
  • Medical Imaging

Background:

  • Glaucoma is a leading cause of irreversible blindness.
  • Accurate estimation of visual field loss progression is crucial for timely intervention.
  • Current methods for predicting glaucoma progression have limitations.

Purpose of the Study:

  • To develop and evaluate a deep learning algorithm for improved estimation of glaucoma progression rates.
  • To enhance the prediction of future visual field loss patterns in glaucoma patients.
  • To compare the performance of the deep learning model against standard clinical metrics.

Main Methods:

  • A generalized variational auto-encoder (VAE) was trained on 29,161 standard automated perimetry (SAP) visual fields from 3,832 glaucoma patients.
  • The VAE learned a low-dimensional representation of visual field data.
  • Model performance was evaluated by comparing its progression rate and prediction accuracy against SAP mean deviation (MD) and point-wise (PW) regression.

Main Results:

  • The VAE detected a significantly higher proportion of progression at 2 and 4 years compared to MD rates (25% vs. 9% and 35% vs. 15%, respectively).
  • The VAE demonstrated significantly improved prediction accuracy over PW regression, with a smaller mean absolute error in predicting future visits (e.g., 5.14 dB vs. 8.07 dB for the 8th visit).
  • The VAE's longitudinal rate of change in latent space effectively captured disease progression.

Conclusions:

  • A deep variational auto-encoder is effective for assessing glaucoma progression rates and trajectories.
  • The VAE offers a generative approach for predicting future visual field damage patterns.
  • This deep learning model shows promise for enhancing clinical management of glaucoma.