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Related Concept Videos

Glaucoma: Overview01:25

Glaucoma: Overview

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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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Advanced glaucoma disease segmentation and classification with grey wolf optimized U -Net++ and capsule networks.

I Govindharaj1, W Deva Priya2, K L S Soujanya3

  • 1Department of Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, Tamil Nadu, 600062, India. govindharaji@veltech.edu.in.

International Ophthalmology
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Summary

This study introduces an automated glaucoma diagnostic system using U-Net++ and CapsNet, achieving 95.1% accuracy for early detection. The advanced tool enhances diagnostic speed and precision, aiding in vision preservation.

Keywords:
Automated diagnosisCapsNetGrey wolf techniquesMedical image segmentationRetinal image analysisVision preservation

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Area of Science:

  • Ophthalmology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Glaucoma is a leading cause of irreversible blindness worldwide.
  • Current screening methods are time-consuming and require expert interpretation, delaying diagnosis and intervention.
  • Early detection is crucial for preserving vision in glaucoma patients.

Purpose of the Study:

  • To develop an automated glaucoma diagnostic system integrating an optimized U-Net++ segmentation model with a Capsule Network (CapsNet) classifier.
  • To enhance segmentation of optic disc and cup regions using the Grey Wolf Optimization Algorithm (GWOA).
  • To achieve accurate glaucoma classification from retinal fundus images.

Main Methods:

  • A two-phase computer-assisted diagnosis (CAD) framework was proposed.
  • An enhanced U-Net++ model, optimized by GWOA, was used for segmenting optic disc and cup regions.
  • A CapsNet architecture was employed for classifying images as glaucomatous or normal.

Main Results:

  • The GWOA-UNet++ and CapsNet framework achieved 95.1% accuracy in segmentation and classification.
  • The system outperformed existing benchmark models in accuracy, sensitivity, specificity, precision, and F1-score.
  • The model demonstrated robustness against image quality variations and optic disc size differences.

Conclusions:

  • The automated system offers enhanced diagnostic accuracy, efficiency, and reliability for early glaucoma detection.
  • This tool can serve as valuable clinical decision support for ophthalmologists.
  • Future work includes validation on diverse datasets and integration into clinical workflows for scalable deployment.