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Nerve Fibers

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Forecasting Retinal Nerve Fiber Layer Thickness from Multimodal Temporal Data Incorporating OCT Volumes.

Ophthalmology. Glaucoma
PURPOSE: The purpose of this study was to develop a machine learning model to forecast future circumpapillary retinal nerve fiber layer (cpRNFL) thickness in eyes of healthy, glaucoma suspect, and glaucoma participants from multimodal temporal data.

Machine Learning Models for Diagnosing Glaucoma from Retinal Nerve Fiber Layer Thickness Maps.

Ophthalmology. Glaucoma
PURPOSE: To assess the diagnostic accuracy of multiple machine learning models using full retinal nerve fiber layer (RNFL) thickness maps in detecting glaucoma.

Discriminating glaucomatous and compressive optic neuropathy on spectral-domain optical coherence tomography with deep learning classifier.

The British journal of ophthalmology
BACKGROUND/AIMS: To assess the performance of a deep learning classifier for differentiation of glaucomatous optic neuropathy (GON) from compressive optic neuropathy (CON) based on ganglion cell-inner plexiform layer (GCIPL) and retinal nerve fibre l...

Diagnosing Glaucoma With Spectral-Domain Optical Coherence Tomography Using Deep Learning Classifier.

Journal of glaucoma
UNLABELLED: PRéCIS:: A spectral-domain optical coherence tomography (SD-OCT) based deep learning system detected glaucomatous structural change with high sensitivity and specificity. It outperformed the clinical diagnostic parameters in discriminatin...

Automated Nerve Fibres Identification and Morphometry Analysis with Neural Network Based Tool in MATLAB.

Studies in health technology and informatics
Analyses of nerve histology are core assays in basic and applied research and even in clinical setting. Detailed report on nerve morphology may unbiased indicate the current state of a peripheral nerve. Manual method requires trained technician and i...

Deep learning model to predict visual field in central 10° from optical coherence tomography measurement in glaucoma.

The British journal of ophthalmology
BACKGROUND/AIM: To train and validate the prediction performance of the deep learning (DL) model to predict visual field (VF) in central 10° from spectral domain optical coherence tomography (SD-OCT).

Automated Nerve Fibres Identification and Morphometry Analysis with Neural Network Based Tool in MATLAB.

Studies in health technology and informatics
Analyses of nerve histology are core assays in basic and applied research and even in clinical setting. Detailed report on nerve morphology may unbiasedly indicate the current state of a peripheral nerve. Manual method requires trained technician and...

Pyramid-Shape Crossings and Intercrossing Fibers Are Key Elements for Construction of the Neural Network in the Superficial White Matter of the Human Cerebrum.

Cerebral cortex (New York, N.Y. : 1991)
Structural analysis of the superficial white matter is prerequisite for the understanding of highly integrated functions of the human cerebral cortex. However, the principal components, U-fibers, have been regarded as simple wires to connect adjacent...