AIMC Topic: Retinal Ganglion Cells

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Prediction of Visual Field Progression with Baseline and Longitudinal Structural Measurements Using Deep Learning.

American journal of ophthalmology
PURPOSE: Identifying glaucoma patients at high risk of progression based on widely available structural data is an unmet task in clinical practice. We test the hypothesis that baseline or serial structural measures can predict visual field (VF) progr...

Early inner plexiform layer thinning and retinal nerve fiber layer thickening in excitotoxic retinal injury using deep learning-assisted optical coherence tomography.

Acta neuropathologica communications
Excitotoxicity from the impairment of glutamate uptake constitutes an important mechanism in neurodegenerative diseases such as Alzheimer's, multiple sclerosis, and Parkinson's disease. Within the eye, excitotoxicity is thought to play a critical rol...

Prediction and Detection of Glaucomatous Visual Field Progression Using Deep Learning on Macular Optical Coherence Tomography.

Journal of glaucoma
PRCIS: A deep learning model trained on macular OCT imaging studies detected clinically significant functional glaucoma progression and was also able to predict future progression.

Deep learning visual field global index prediction with optical coherence tomography parameters in glaucoma patients.

Scientific reports
The aim of this study was to predict three visual filed (VF) global indexes, mean deviation (MD), pattern standard deviation (PSD), and visual field index (VFI), from optical coherence tomography (OCT) parameters including Bruch's Membrane Opening-Mi...

Deep Learning Estimation of 10-2 Visual Field Map Based on Macular Optical Coherence Tomography Angiography Measurements.

American journal of ophthalmology
PURPOSE: To develop deep learning (DL) models estimating the central visual field (VF) from optical coherence tomography angiography (OCTA) vessel density (VD) measurements.

Multimodal Deep Learning Classifier for Primary Open Angle Glaucoma Diagnosis Using Wide-Field Optic Nerve Head Cube Scans in Eyes With and Without High Myopia.

Journal of glaucoma
PRCIS: An optical coherence tomography (OCT)-based multimodal deep learning (DL) classification model, including texture information, is introduced that outperforms single-modal models and multimodal models without texture information for glaucoma di...

The macular retinal ganglion cell layer as a biomarker for diagnosis and prognosis in multiple sclerosis: A deep learning approach.

Acta ophthalmologica
PURPOSE: The macular ganglion cell layer (mGCL) is a strong potential biomarker of axonal degeneration in multiple sclerosis (MS). For this reason, this study aims to develop a computer-aided method to facilitate diagnosis and prognosis in MS.

Development of a deep learning system to detect glaucoma using macular vertical optical coherence tomography scans of myopic eyes.

Scientific reports
Myopia is one of the risk factors for glaucoma, making accurate diagnosis of glaucoma in myopic eyes particularly important. However, diagnosis of glaucoma in myopic eyes is challenging due to the frequent associations of distorted optic disc and dis...

Diagnostic ability of macular microvasculature with swept-source OCT angiography for highly myopic glaucoma using deep learning.

Scientific reports
Macular OCT angiography (OCTA) measurements have been reported to be useful for glaucoma diagnostics. However, research on highly myopic glaucoma is lacking, and the diagnostic value of macular OCTA measurements versus OCT parameters remains inconclu...