Glaucoma

Glaucoma screening: where are we and where do we need to go?

PURPOSE OF REVIEW: Current recommendations for glaucoma screening are decidedly neutral. No studies ...

Characterization of Central Visual Field Loss in End-stage Glaucoma by Unsupervised Artificial Intelligence.

IMPORTANCE: Although the central visual field (VF) in end-stage glaucoma may substantially vary amon...

Artificial Intelligence for Cataract Detection and Management.

The rising popularity of artificial intelligence (AI) in ophthalmology is fuelled by the ever-increa...

Artificial Intelligence in Ophthalmology: Evolutions in Asia.

Artificial intelligence (AI) has been studied in ophthalmology since availability of digital informa...

Diagnosis of Glaucoma on Retinal Fundus Images Using Deep Learning: Detection of Nerve Fiber Layer Defect and Optic Disc Analysis.

Early detection of glaucoma is important to slow down progression of the disease and to prevent tota...

Accuracy of Kalman Filtering in Forecasting Visual Field and Intraocular Pressure Trajectory in Patients With Ocular Hypertension.

IMPORTANCE: Techniques that properly identify patients in whom ocular hypertension (OHTN) is likely ...

Finding Glaucoma in Color Fundus Photographs Using Deep Learning.

Enhancing the Accuracy of Glaucoma Detection from OCT Probability Maps using Convolutional Neural Networks.

We describe and assess convolutional neural network (CNN) models for detection of glaucoma based upo...

Conditional Adversarial Transfer for Glaucoma Diagnosis.

Deep learning has achieved great success in image classification task when given sufficient labeled ...

Automated Glaucoma Screening from Retinal Fundus Image Using Deep Learning.

Glaucoma is the second leading cause of blindness worldwide. This paper proposes an automated glauco...

Screening Glaucoma With Red-free Fundus Photography Using Deep Learning Classifier and Polar Transformation.

UNLABELLED: PRéCIS:: The novel proposed algorithm using deep learning classifier and polar transform...

Artificial intelligence in glaucoma.

PURPOSE OF REVIEW: The use of computers has become increasingly relevant to medical decision-making,...

An Artificial Intelligence Approach to Detect Visual Field Progression in Glaucoma Based on Spatial Pattern Analysis.

PURPOSE: To detect visual field (VF) progression by analyzing spatial pattern changes.

A Unified Optic Nerve Head and Optic Cup Segmentation Using Unsupervised Neural Networks for Glaucoma Screening.

Segmentation of retinal anatomical features such as optic nerve head (ONH) and optic cup, the bright...

Joint Optic Disc and Cup Segmentation Based on Multi-Label Deep Network and Polar Transformation.

Glaucoma is a chronic eye disease that leads to irreversible vision loss. The cup to disc ratio (CDR...

Deep-learning Classifier With an Ultrawide-field Scanning Laser Ophthalmoscope Detects Glaucoma Visual Field Severity.

PURPOSE: To evaluate the accuracy of detecting glaucoma visual field defect severity using deep-lear...

Retinal Nerve Fiber Layer Features Identified by Unsupervised Machine Learning on Optical Coherence Tomography Scans Predict Glaucoma Progression.

PURPOSE: To apply computational techniques to wide-angle swept-source optical coherence tomography (...

Hybrid Deep Learning on Single Wide-field Optical Coherence tomography Scans Accurately Classifies Glaucoma Suspects.

PURPOSE: Existing summary statistics based upon optical coherence tomographic (OCT) scans and/or vis...

Comparison of Intravitreal Bevacizumab and Intravitreal Diclofenac in the Treatment of Diabetic Macular Edema: a 6-month Follow-up.

The aim of this study was to compare the effect of intravitreal diclofenac, a non-steroidal anti-inf...

Automatic Identification of Glaucoma Using Deep Learning Methods.

This paper proposes an automatic classification method to detect glaucoma in fundus images. The meth...

Intraoperative Management of Increased Intraocular Pressure in a Patient with Glaucoma Undergoing Robotic Prostatectomy in Trendelenburg Position.