Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Glaucoma: Overview

Glaucoma: Overview

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...

You might also read

Related Articles

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

Sort by

Same author

Durability and Seasonal Variation in the Effectiveness of Nirsevimab over Three Seasons in Connecticut.

medRxiv : the preprint server for health sciences·2026

Same author

Lineage-specific transmission and spatial clustering of Mycobacterium tuberculosis in Kaohsiung, Taiwan, in 2019-23: a population-based genomic study.

The Lancet. Microbe·2026

Same author

Tropical cyclone exposure and risk of adverse birth outcomes in urban and rural areas of Georgia.

Environmental research communications·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

Same author

Utilizing virus genomic surveillance to predict vaccine effectiveness.

PLoS computational biology·2026

Same journal

Instrumental Variable Estimation of Marginal Structural Mean Models for Time-Varying Treatment.

Journal of the American Statistical Association·2026

Same journal

Semiparametric Joint Modeling for Survival Analysis with Longitudinal Covariates.

Journal of the American Statistical Association·2026

Same journal

Dimension Reduction for Large-Scale Federated Data: Statistical Rate and Asymptotic Inference.

Journal of the American Statistical Association·2026

Same journal

Facilitating Heterogeneous Effect Estimation via Statistically Efficient Categorical Modifiers.

Journal of the American Statistical Association·2026

Same journal

Nonparametric Density Estimation of a Long-Term Trend from Repeated Semicontinuous Data.

Journal of the American Statistical Association·2026

Same journal

Functional Integrative Bayesian Analysis of High-dimensional Multiplatform Clinicogenomic Data.

Journal of the American Statistical Association·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jan 4, 2026

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

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

Published on: May 25, 2020

Diagnosing Glaucoma Progression with Visual Field Data Using a Spatiotemporal Boundary Detection Method.

Samuel I Berchuck¹, Jean-Claude Mwanza², Joshua L Warren³

¹Department of Statistical Science and Forge, Duke University, NC 27708 (sib2@duke.edu).

Journal of the American Statistical Association

|October 31, 2019

Summary

This summary is machine-generated.

This study introduces a novel spatiotemporal model to improve glaucoma progression diagnosis using visual field data. The method enhances vision loss detection by considering optic disc anatomy, outperforming existing spatial techniques.

Keywords:

Areal wombling Bayesian methods Conditional autoregressive models Dissimilarity metric

More Related Videos

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

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

Published on: July 21, 2020

Trabecular Meshwork Response to Pressure Elevation in the Living Human Eye

Trabecular Meshwork Response to Pressure Elevation in the Living Human Eye

Published on: June 20, 2015

Related Experiment Videos

Last Updated: Jan 4, 2026

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

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

Published on: May 25, 2020

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

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

Published on: July 21, 2020

Trabecular Meshwork Response to Pressure Elevation in the Living Human Eye

Trabecular Meshwork Response to Pressure Elevation in the Living Human Eye

Published on: June 20, 2015

Area of Science:

Ophthalmology
Medical Statistics
Computer Vision

Background:

Diagnosing glaucoma progression is crucial for preventing irreversible vision loss.
Current methods often rely on longitudinal visual field (VF) data, which possess complex spatiotemporal structures.
Advanced statistical approaches are necessary for accurate clinical determinations of glaucoma progression.

Purpose of the Study:

To introduce a novel spatiotemporal boundary detection model for diagnosing glaucoma progression.
To leverage the optic disc's anatomy to define the spatial structure of VF data over time.
To improve the diagnostic accuracy of vision loss in glaucoma patients.

Main Methods:

Developed a spatiotemporal boundary detection model integrating optic disc anatomy.
Applied the model to VF data from the Vein Pulsation Study Trial in Glaucoma and the Lions Eye Institute registry.
Conducted simulations to compare the new method against existing spatial techniques.

Main Results:

The proposed model offers novel insights into vision loss patterns.
The method demonstrates improved diagnosis of glaucoma progression compared to current approaches.
Simulations indicate the spatiotemporal model's superiority over existing spatial methods for VF data analysis.

Conclusions:

The novel spatiotemporal boundary detection model enhances glaucoma progression diagnosis.
Integrating anatomical information improves the analysis of complex VF data.
The womblR R package provides an implementation of this advanced methodology.