AIMC Topic: Anterior Eye Segment

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Prediction of Phakic Intraocular Lens Vault Using Machine Learning of Anterior Segment Optical Coherence Tomography Metrics.

American journal of ophthalmology
PURPOSE: To compare the achieved vault using the conventional manufacturer's nomogram and the predicted vault using machine learning, in a large cohort of eyes undergoing posterior chamber phakic intraocular lens (EVO implantable collamer lens [ICL];...

Angle-closure assessment in anterior segment OCT images via deep learning.

Medical image analysis
Precise characterization and analysis of anterior chamber angle (ACA) are of great importance in facilitating clinical examination and diagnosis of angle-closure disease. Currently, the gold standard for diagnostic angle assessment is observation of ...

Deep learning algorithms to isolate and quantify the structures of the anterior segment in optical coherence tomography images.

The British journal of ophthalmology
BACKGROUND/AIMS: Accurate isolation and quantification of intraocular dimensions in the anterior segment (AS) of the eye using optical coherence tomography (OCT) images is important in the diagnosis and treatment of many eye diseases, especially angl...

Artificial intelligence for anterior segment diseases: Emerging applications in ophthalmology.

The British journal of ophthalmology
With the advancement of computational power, refinement of learning algorithms and architectures, and availability of big data, artificial intelligence (AI) technology, particularly with machine learning and deep learning, is paving the way for 'inte...

Deep Learning Classifiers for Automated Detection of Gonioscopic Angle Closure Based on Anterior Segment OCT Images.

American journal of ophthalmology
PURPOSE: To develop and test deep learning classifiers that detect gonioscopic angle closure and primary angle closure disease (PACD) based on fully automated analysis of anterior segment OCT (AS-OCT) images.

A Deep Learning System for Automated Angle-Closure Detection in Anterior Segment Optical Coherence Tomography Images.

American journal of ophthalmology
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...

Artificial Intelligence Aided Analysis of Anterior Segment Optical Coherence Tomography Imaging to Monitor the Device-Cornea Joint After Synthetic Cornea Implantation.

Translational vision science & technology
PURPOSE: The purpose of this study was to assess the utility of artificial intelligence (AI) assisted analysis of anterior segment optical coherence tomography (AS-OCT) imaging of the device-cornea joint in predicting outcomes of an intrastromal synt...

Development of machine learning-based models for vault prediction in implantable collamer lens surgery according to implant orientation.

Journal of cataract and refractive surgery
PURPOSE: To develop a prediction model based on machine learning to calculate the postoperative vault and the ideal implantable collamer lens (ICL) size, considering for the first time the implantation orientation in a White population.

Automatic Anterior Chamber Angle Classification Using Deep Learning System and Anterior Segment Optical Coherence Tomography Images.

Translational vision science & technology
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).