AIMC Topic: Glaucoma, Angle-Closure
Clear Filters Showing 21 to 28 of 28 articles
A Deep Learning System for Automated Angle-Closure Detection in Anterior Segment Optical Coherence Tomography Images.
American journal of ophthalmology
Mar 6, 2019
PURPOSE: Anterior segment optical coherence tomography (AS-OCT) provides an objective imaging modality for visually identifying anterior segment structures. An automated detection system could assist ophthalmologists in interpreting AS-OCT images for...
Learning ECOC Code Matrix for Multiclass Classification with Application to Glaucoma Diagnosis.
Journal of medical systems
Jan 21, 2016
Classification of different mechanisms of angle closure glaucoma (ACG) is important for medical diagnosis. Error-correcting output code (ECOC) is an effective approach for multiclass classification. In this study, we propose a new ensemble learning m...
Deep learning-based automatic differentiation of acute angle closure with or without zonulopathy using ultrasound biomicroscopy: a comparison of diagnostic performance with ophthalmologists.
BMJ open ophthalmology
May 22, 2025
OBJECTIVE: This study aims to develop ultrasound biomicroscopy (UBM)-based artificial intelligence (AI) models for preoperative differentiation of acute angle closure (AAC) with or without zonulopathy and to compare their comprehensive diagnostic per...
[Primary angle closure suspects: application of machine learning method for substantiation of close monitoring].
Vestnik oftalmologii
Jan 1, 2025
UNLABELLED: One of the priority areas in healthcare is the concept of predictive, preventive and personalized medicine, which is based on an individualized approach to the patient, including before the onset of diseases such as glaucoma.
[Application of artificial intelligence methods in the diagnosis and treatment of primary angle-closure disease].
Vestnik oftalmologii
Jan 1, 2024
This article reviews literature on the use of artificial intelligence (AI) methods for the diagnosis and treatment of primary angle-closure disease (PACD). The review describes how AI techniques enhance the efficiency of population screening for ante...
A Deep Learning System for Automatic Assessment of Anterior Chamber Angle in Ultrasound Biomicroscopy Images.
Translational vision science & technology
Sep 1, 2021
PURPOSE: To develop and assess a deep learning system that automatically detects angle closure and quantitatively measures angle parameters from ultrasound biomicroscopy (UBM) images using a deep learning algorithm.
Automatic Localization of the Scleral Spur Using Deep Learning and Ultrasound Biomicroscopy.
Translational vision science & technology
Aug 2, 2021
PURPOSE: The purpose of this study was to develop a convolutional neural network (CNN) for automated localization of the scleral spur in ultrasound biomicroscopy (UBM) images of open-angle eyes.
Automatic Anterior Chamber Angle Classification Using Deep Learning System and Anterior Segment Optical Coherence Tomography Images.
Translational vision science & technology
May 3, 2021
PURPOSE: The purpose of this study was to develop a software package for the automatic classification of anterior chamber angle using anterior segment optical coherence tomography (AS-OCT).
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