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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...
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Open Angle Glaucoma: Treatment01:27

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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...
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Angle Closure Glaucoma: Treatment01:28

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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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At the molecular level, visual signals trigger transformations in photopigment molecules, resulting in changes in the photoreceptor cell's membrane potential. The photon's energy level is denoted by its wavelength, with each specific wavelength of visible light associated with a distinct color. The spectral range of visible light, classified as electromagnetic radiation, spans from 380 to 720 nm. Electromagnetic radiation wavelengths exceeding 720 nm fall under the infrared category,...
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Related Experiment Video

Updated: Jan 9, 2026

Full-Circle Cauterization of Limbal Vascular Plexus for Surgically Induced Glaucoma in Rodents
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OptiGuard: Generalized, Attention-Driven & Explainable Glaucoma Classification.

Syed Safi Ullah Shah, Muhammad Huzaifa, Humza Khawar Khan Tareen

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |December 3, 2025
    PubMed
    Summary

    OptiGuard, an AI system using retinal images, aids in early glaucoma detection. It offers accurate diagnosis and explainable results, improving accessibility and trust in eye care.

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    Area of Science:

    • Ophthalmology
    • Artificial Intelligence
    • Medical Imaging

    Background:

    • Glaucoma causes irreversible optic nerve damage and vision loss, often detected late due to asymptomatic progression.
    • Conventional diagnostic tools like OCT and VFT have accessibility limitations, delaying critical early interventions.
    • Increasing patient numbers and a shortage of ophthalmologists necessitate advanced, automated diagnostic solutions.

    Purpose of the Study:

    • To introduce OptiGuard, a deep learning-based Computer-Aided Diagnosis (CAD) system for automated glaucoma detection.
    • To address limitations of existing automated systems, including dataset scarcity, poor generalizability, and lack of explainability.
    • To develop a user-friendly system with enhanced transparency for healthcare professionals.

    Main Methods:

    • Utilized the G1020 dataset for state-of-the-art Optic Disc and Cup segmentation.
    • Employed the SMDG-19 dataset for robust glaucoma classification.
    • Developed a deep learning model integrated into an intuitive web interface.

    Main Results:

    • Achieved state-of-the-art results in Optic Disc and Cup segmentation.
    • Developed a generalized glaucoma classification model with strong cross-dataset performance.
    • Integrated visual and quantitative explanations for enhanced transparency.

    Conclusions:

    • OptiGuard offers a promising, accessible, and explainable automated solution for glaucoma diagnosis.
    • The system demonstrates strong performance and generalizability, addressing key challenges in automated eye care.
    • OptiGuard has the potential to improve early glaucoma detection rates and foster trust in AI-driven diagnostics.