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

1.4K
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...
1.4K
Open Angle Glaucoma: Treatment01:27

Open Angle Glaucoma: Treatment

989
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...
989
Angle Closure Glaucoma: Treatment01:28

Angle Closure Glaucoma: Treatment

1.2K
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...
1.2K
Dehydration Synthesis01:15

Dehydration Synthesis

149.4K
Overview
Dehydration synthesis (also called a condensation reaction) is the chemical process in which two molecules covalently link together to form a new molecule, along with the release of a water molecule. Many physiologically important compounds form by dehydration synthesis reactions, such as complex carbohydrates, proteins, DNA, and RNA.
Synthesis of carbohydrates
Sugar molecules are covalently linked together by dehydration synthesis. During the reaction, the hydroxyl (-OH) group from...
149.4K
Avoidance Learning and Learned Helplessness01:14

Avoidance Learning and Learned Helplessness

2.6K
Avoidance learning and learned helplessness are critical concepts in understanding behavioral responses to negative stimuli.
Avoidance learning occurs when an organism learns that a specific behavior can prevent an unpleasant outcome. For example, a student who receives a bad grade may start studying harder to avoid future poor grades. This behavior persists even when the negative outcome is no longer present. Avoidance learning is powerful because it maintains behavior in the absence of the...
2.6K
Synthesis and Decomposition Reactions02:17

Synthesis and Decomposition Reactions

38.1K
Synthesis and decomposition are two types of redox reactions. Synthesis means to make something, whereas decomposition means to break something. The reactions are accompanied by chemical and energy changes. 
38.1K

You might also read

Related Articles

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

Sort by
Same author

Automatic Evaluation of Small Bowel Cleanliness in Capsule Endoscopy: A Comparative Study of Four Preparations using Artificial Intelligence.

Endoscopy international open·2026
Same author

CeraMIRScan: Mid-infrared OCT Scan Dataset for Ceramic Quality Assessment.

Scientific data·2026
Same author

Artificial intelligence for detecting fetal orofacial clefts and advancing medical education.

Nature communications·2026
Same author

Multi-omic analysis of deep learning-derived phenotypes links ophthalmic imaging to cardiovascular and neurological traits.

Nature cardiovascular research·2026
Same author

From pixels to polygons: A survey of deep learning approaches for medical image-to-mesh reconstruction.

Medical image analysis·2026
Same author

Fourier-Net+: Band-Limited Spatial Representation for Efficient Medical Image Registration.

IEEE transactions on neural networks and learning systems·2026

Related Experiment Video

Updated: Jan 28, 2026

Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis
09:16

Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis

Published on: June 18, 2020

7.3K

Retinal Image Synthesis and Semi-Supervised Learning for Glaucoma Assessment.

Andres Diaz-Pinto, Adrian Colomer, Valery Naranjo

    IEEE Transactions on Medical Imaging
    |March 8, 2019
    PubMed
    Summary

    This study introduces a novel deep convolutional generative adversarial network (GAN) system for glaucoma assessment. The system synthesizes realistic retinal images and accurately classifies them, aiding in early disease detection.

    More Related Videos

    Analyzing Mitochondrial Morphology Through Simulation Supervised Learning
    12:06

    Analyzing Mitochondrial Morphology Through Simulation Supervised Learning

    Published on: March 3, 2023

    4.7K
    In Vivo Dynamics of Retinal Microglial Activation During Neurodegeneration: Confocal Ophthalmoscopic Imaging and Cell Morphometry in Mouse Glaucoma
    12:48

    In Vivo Dynamics of Retinal Microglial Activation During Neurodegeneration: Confocal Ophthalmoscopic Imaging and Cell Morphometry in Mouse Glaucoma

    Published on: May 11, 2015

    11.1K

    Related Experiment Videos

    Last Updated: Jan 28, 2026

    Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis
    09:16

    Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis

    Published on: June 18, 2020

    7.3K
    Analyzing Mitochondrial Morphology Through Simulation Supervised Learning
    12:06

    Analyzing Mitochondrial Morphology Through Simulation Supervised Learning

    Published on: March 3, 2023

    4.7K
    In Vivo Dynamics of Retinal Microglial Activation During Neurodegeneration: Confocal Ophthalmoscopic Imaging and Cell Morphometry in Mouse Glaucoma
    12:48

    In Vivo Dynamics of Retinal Microglial Activation During Neurodegeneration: Confocal Ophthalmoscopic Imaging and Cell Morphometry in Mouse Glaucoma

    Published on: May 11, 2015

    11.1K

    Area of Science:

    • Ophthalmology
    • Medical Imaging
    • Artificial Intelligence

    Background:

    • Glaucoma diagnosis relies on analyzing optic disc morphology.
    • Limited labeled datasets hinder the development of automated diagnostic tools.
    • Generative Adversarial Networks (GANs) show promise in image synthesis and semi-supervised learning.

    Purpose of the Study:

    • To develop a novel retinal image synthesizer and semi-supervised learning method for glaucoma assessment.
    • To leverage deep convolutional GANs for improved automated glaucoma detection.
    • To train a system on a large, publicly available dataset of retinal images.

    Main Methods:

    • Utilized deep convolutional GANs for training a retinal image synthesizer and a semi-supervised classifier.
    • Employed a dataset of 86,926 publicly available retinal images, automatically cropped around the optic disc.
    • Evaluated synthetic image quality using t-SNE plots and anatomical consistency metrics.

    Main Results:

    • The developed system successfully generates realistic, cropped retinal images.
    • The glaucoma classifier achieved high accuracy (AUC = 0.9017) in distinguishing between glaucomatous and normal images.
    • The system can automatically provide glaucoma labels for generated synthetic images.

    Conclusions:

    • The proposed GAN-based system is effective for both synthetic retinal image generation and automated glaucoma classification.
    • This approach can generate an unlimited supply of labeled retinal images for further research and development.
    • The system demonstrates significant potential for advancing automated glaucoma screening and monitoring.