AIMC Topic: Nerve Fibers
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Deep learning approaches to predict 10-2 visual field from wide-field swept-source optical coherence tomography en face images in glaucoma.
Scientific reports
Dec 5, 2022
Close monitoring of central visual field (VF) defects with 10-2 VF helps prevent blindness in glaucoma. We aimed to develop a deep learning model to predict 10-2 VF from wide-field swept-source optical coherence tomography (SS-OCT) images. Macular ga...
Deep Learning Estimation of 10-2 Visual Field Map Based on Circumpapillary Retinal Nerve Fiber Layer Thickness Measurements.
American journal of ophthalmology
Nov 1, 2022
PURPOSE: To estimate central 10-degree visual field (VF) map from spectral-domain optical coherence tomography (SD-OCT) retinal nerve fiber layer thickness (RNFL) measurements in glaucoma with artificial intelligence.
Measurement of retinal nerve fiber layer thickness with a deep learning algorithm in ischemic optic neuropathy and optic neuritis.
Scientific reports
Oct 12, 2022
This work aims at determining the ability of a deep learning (DL) algorithm to measure retinal nerve fiber layer (RNFL) thickness from optical coherence tomography (OCT) scans in anterior ischemic optic neuropathy (NAION) and demyelinating optic neur...
A Deep Learning Approach to Improve Retinal Structural Predictions and Aid Glaucoma Neuroprotective Clinical Trial Design.
Ophthalmology. Glaucoma
Aug 28, 2022
PURPOSE: To investigate the efficacy of a deep learning regression method to predict macula ganglion cell-inner plexiform layer (GCIPL) and optic nerve head (ONH) retinal nerve fiber layer (RNFL) thickness for use in glaucoma neuroprotection clinical...
DeepGrading: Deep Learning Grading of Corneal Nerve Tortuosity.
IEEE transactions on medical imaging
Aug 1, 2022
Accurate estimation and quantification of the corneal nerve fiber tortuosity in corneal confocal microscopy (CCM) is of great importance for disease understanding and clinical decision-making. However, the grading of corneal nerve tortuosity remains ...
Deep learning identify retinal nerve fibre and choroid layers as markers of age-related macular degeneration in the classification of macular spectral-domain optical coherence tomography volumes.
Acta ophthalmologica
Mar 1, 2022
Re: Christopher et al.: Deep learning approaches predict glaucomatous visual field damage from OCT optic nerve head en face images and retinal nerve fiber layer thickness maps (Ophthalmology. 2020;127:346-356).
Ophthalmology
Oct 7, 2021
Multimodal Machine Learning Using Visual Fields and Peripapillary Circular OCT Scans in Detection of Glaucomatous Optic Neuropathy.
Ophthalmology
Jul 30, 2021
PURPOSE: To develop and validate a multimodal artificial intelligence algorithm, FusionNet, using the pattern deviation probability plots from visual field (VF) reports and circular peripapillary OCT scans to detect glaucomatous optic neuropathy (GON...
Adult
Cross-Sectional Studies
Intraocular Pressure
ROC Curve
Visual Field Tests
Vision Disorders
Nerve Fibers
Algorithms
Optic Nerve Diseases
Multimodal Imaging
Retinal Ganglion Cells
Female
Humans
Male
Glaucoma, Open-Angle
Area Under Curve
Visual Fields
Aged
Middle Aged
Machine Learning
Tomography, Optical Coherence
Learning to estimate the fiber orientation distribution function from diffusion-weighted MRI.
NeuroImage
Jun 26, 2021
Estimation of white matter fiber orientation distribution function (fODF) is the essential first step for reliable brain tractography and connectivity analysis. Most of the existing fODF estimation methods rely on sub-optimal physical models of the d...
Predicting Glaucoma Development With Longitudinal Deep Learning Predictions From Fundus Photographs.
American journal of ophthalmology
Jan 7, 2021
PURPOSE: To assess whether longitudinal changes in a deep learning algorithm's predictions of retinal nerve fiber layer (RNFL) thickness based on fundus photographs can predict future development of glaucomatous visual field defects.
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