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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...

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Open Angle Glaucoma: Treatment

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.
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Angle Closure Glaucoma: Treatment

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...

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Related Experiment Video

Updated: Aug 8, 2025

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

Wavelet image scattering based glaucoma detection.

Hafeez Alani Agboola¹, Jesuloluwa Emmanuel Zaccheus²

¹Afe Babalola University, Ado-Ekiti, Nigeria. hafeezagboola@abuad.edu.ng.

BMC Biomedical Engineering

|March 2, 2023

Summary

This summary is machine-generated.

A novel wavelet scattering network achieved 98% accuracy in detecting glaucoma from retinal images. This AI approach automatically learns features, offering a promising, efficient alternative for automated medical image analysis and diagnosis.

Keywords:

Glaucoma detection Retinal fundus image Scattering features Wavelet scattering network

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Last Updated: Aug 8, 2025

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Published on: June 2, 2010

Area of Science:

Ophthalmology
Medical Imaging
Artificial Intelligence

Background:

The demand for accessible healthcare drives AI integration in medicine, particularly for complex biomedical image analysis.
Automated diagnosis from retinal fundus images is challenging due to intricate patterns.
Traditional methods rely on manual feature extraction from pre-processed images.

Purpose of the Study:

To evaluate the efficacy of a Wavelet Scattering Network for automated feature extraction and glaucoma detection using retinal fundus images.
To investigate the impact of network parameters and image types on diagnostic accuracy.
To compare the performance of this AI method against conventional approaches.

Main Methods:

Applied an Invariant Scattering Convolution Network (Wavelet Scattering Network) to the RIM-ONE DL dataset.
Utilized a stage-wise decomposition process for automatic feature learning from retinal images.
Developed simple, computationally inexpensive classification algorithms based on learned features.

Main Results:

Achieved a maximum detection correctness of 98% on a held-out test set.
Demonstrated that detection accuracy is sensitive to scattering network parameters and 2-D channel image types.
The automatically extracted features proved effective for glaucoma diagnosis.

Conclusions:

The Wavelet Scattering Network shows significant potential for automated glaucoma detection.
This method offers a viable alternative to traditional feature engineering in medical image analysis.
Further comparison with Convolutional Neural Networks highlights the proposed method's capabilities.