AIMC Topic: Intraocular Pressure

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Policy-Driven, Multimodal Deep Learning for Predicting Visual Fields from the Optic Disc and OCT Imaging.

Ophthalmology
PURPOSE: To develop and validate a deep learning (DL) system for predicting each point on visual fields (VFs) from disc and OCT imaging and derive a structure-function mapping.

Reproducibility of deep learning based scleral spur localisation and anterior chamber angle measurements from anterior segment optical coherence tomography images.

The British journal of ophthalmology
AIMS: To apply a deep learning model for automatic localisation of the scleral spur (SS) in anterior segment optical coherence tomography (AS-OCT) images and compare the reproducibility of anterior chamber angle (ACA) width between deep learning loca...

Glaucoma disease diagnosis with an artificial algae-based deep learning algorithm.

Medical & biological engineering & computing
Glaucoma disease is optic neuropathy; in glaucoma, the optic nerve is damaged because the long duration of intraocular pressure can be caused blindness. Nowadays, deep learning classification algorithms are widely used to diagnose various diseases. H...

Predicting Visual Fields From Optical Coherence Tomography via an Ensemble of Deep Representation Learners.

American journal of ophthalmology
PURPOSE: To develop and validate a deep learning method of predicting visual function from spectral domain optical coherence tomography (SD-OCT)-derived retinal nerve fiber layer thickness (RNFLT) measurements and corresponding SD-OCT images.

Accurate Identification of the Trabecular Meshwork under Gonioscopic View in Real Time Using Deep Learning.

Ophthalmology. Glaucoma
PURPOSE: Accurate identification of iridocorneal structures on gonioscopy is difficult to master, and errors can lead to grave surgical complications. This study aimed to develop and train convolutional neural networks (CNNs) to accurately identify t...

Open-source deep learning-based automatic segmentation of mouse Schlemm's canal in optical coherence tomography images.

Experimental eye research
The purpose of this study was to develop an automatic deep learning-based approach and corresponding free, open-source software to perform segmentation of the Schlemm's canal (SC) lumen in optical coherence tomography (OCT) scans of living mouse eyes...

Deep Learning Image Analysis of Optical Coherence Tomography Angiography Measured Vessel Density Improves Classification of Healthy and Glaucoma Eyes.

American journal of ophthalmology
PURPOSE: To compare convolutional neural network (CNN) analysis of en face vessel density images to gradient boosting classifier (GBC) analysis of instrument-provided, feature-based optical coherence tomography angiography (OCTA) vessel density measu...

Generalisability and performance of an OCT-based deep learning classifier for community-based and hospital-based detection of gonioscopic angle closure.

The British journal of ophthalmology
PURPOSE: To assess the generalisability and performance of a deep learning classifier for automated detection of gonioscopic angle closure in anterior segment optical coherence tomography (AS-OCT) images.

Anterior segment biometric measurements explain misclassifications by a deep learning classifier for detecting gonioscopic angle closure.

The British journal of ophthalmology
BACKGROUND/AIMS: To identify biometric parameters that explain misclassifications by a deep learning classifier for detecting gonioscopic angle closure in anterior segment optical coherence tomography (AS-OCT) images.