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Explainable Deep Learning for Glaucomatous Visual Field Prediction: Artifact Correction Enhances Transformer Models.
Transl Vis Sci Technol
January 2025
Department of Biomedical Engineering, Faculty of Engineering, Mahidol University, Nakhon Pathom, Thailand.
Purpose: The purpose of this study was to develop a deep learning approach that restores artifact-laden optical coherence tomography (OCT) scans and predicts functional loss on the 24-2 Humphrey Visual Field (HVF) test.
Methods: This cross-sectional, retrospective study used 1674 visual field (VF)-OCT pairs from 951 eyes for training and 429 pairs from 345 eyes for testing. Peripapillary retinal nerve fiber layer (RNFL) thickness map artifacts were corrected using a generative diffusion model.
Eye Movements and the Intraorbital Subarachnoid Space: Potential Contribution of Altered Cerebrospinal Fluid Pumping in Optic Neuropathies.
Invest Ophthalmol Vis Sci
January 2025
Department of Ophthalmology, University of California, Los Angeles, California, United States.
Purpose: The optic nerve (ON) is mechanically perturbed by eye movements that shift cerebrospinal fluid (CSF) within its surrounding dural sheath. This study compared changes in ON length and CSF volume within the intraorbital ON sheath caused by eye movements in healthy subjects and patients with optic neuropathies.
Methods: Twenty-one healthy controls were compared with 11 patients having primary open angle glaucoma (POAG) at normal intraocular pressure (IOP), and 11 with chronic non-arteritic anterior ischemic optic neuropathy (NA-AION).
Enhancing ophthalmology education through a mobile flipped classroom: a new teaching method.
BMC Res Notes
January 2025
Department of Health Information Technology and Management, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Objective: Glaucoma is a major cause of irreversible blindness globally. Optical coherence tomography (OCT) aids early glaucoma diagnosis. Interpreting OCT scans requires familiarity with the technology and image analysis.
View Article and Find Full Text PDFDeep learning-based anterior segment identification and parameter assessment of primary angle closure disease in ultrasound biomicroscopy images.
BMJ Open Ophthalmol
January 2025
Department of Ophthalmology, Peking University People's Hospital, Beijing, China
Purpose: To develop an artificial intelligence algorithm to automatically identify the anterior segment structures and assess multiple parameters of primary angle closure disease (PACD) in ultrasound biomicroscopy (UBM) images.
Design: Development and validation of an artificial intelligence algorithm for UBM images.
Methods: 2339 UBM images from 592 subjects were collected for algorithm development.
A Case of Freeman-Sheldon Syndrome With Glaucoma Successfully Treated by Trabeculotomy Using the Kahook Dual Blade.
Cureus
December 2024
Department of Ophthalmology and Visual Science, Nagoya City University Graduate School of Medical Sciences, Nagoya, JPN.
This case study details a 41-year-old male patient with Freeman-Sheldon syndrome (FSS) who presented with ocular hypertension. The intraocular pressure (IOP) in his right eye progressively increased over time, leading to visual field loss, culminating in a diagnosis of juvenile-onset open-angle glaucoma (JOAG). Despite conventional medical therapies, adequate IOP control was not achieved, necessitating his referral to Nagoya City University Hospital.
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