AIMC Topic: Nerve Fibers

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Machine learning classifiers-based prediction of normal-tension glaucoma progression in young myopic patients.

Japanese journal of ophthalmology Dec 17, 2019
PURPOSE: To assess the performance of machine learning classifiers for prediction of progression of normal-tension glaucoma (NTG) in young myopic patients.
Gonioscopy Slit Lamp Microscopy Low Tension Glaucoma Disease Progression Myopia Diagnosis, Computer-Assisted ROC Curve Area Under Curve Tomography, Optical Coherence Nerve Fibers Retinal Ganglion Cells Visual Fields Visual Field Tests Young Adult Adult Cross-Sectional Studies Intraocular Pressure Male Humans Machine Learning Female
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Detecting glaucoma based on spectral domain optical coherence tomography imaging of peripapillary retinal nerve fiber layer: a comparison study between hand-crafted features and deep learning model.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie Dec 7, 2019
PURPOSE: To develop a deep learning (DL) model for automated detection of glaucoma and to compare diagnostic capability against hand-craft features (HCFs) based on spectral domain optical coherence tomography (SD-OCT) peripapillary retinal nerve fibe...
Prospective Studies Female Aged Aged, 80 and over Young Adult Humans Glaucoma Adolescent Tomography, Optical Coherence Nerve Fibers Optic Disk Retinal Ganglion Cells Visual Fields Adult Intraocular Pressure Male Middle Aged Deep Learning
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Human Versus Machine: Comparing a Deep Learning Algorithm to Human Gradings for Detecting Glaucoma on Fundus Photographs.

American journal of ophthalmology Nov 12, 2019
PURPOSE: To compare the diagnostic performance of human gradings vs predictions provided by a machine-to-machine (M2M) deep learning (DL) algorithm trained to quantify retinal nerve fiber layer (RNFL) damage on fundus photographs.
Retinal Ganglion Cells Visual Fields Visual Field Tests Optic Nerve Diseases Photography Vision Disorders Area Under Curve Tomography, Optical Coherence Fundus Oculi Nerve Fibers Physical Examination Glaucoma, Open-Angle Gonioscopy Algorithms Retrospective Studies Female Aged Cross-Sectional Studies Intraocular Pressure Male Middle Aged Deep Learning ROC Curve Humans
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An artificial intelligence-based deep learning algorithm for the diagnosis of diabetic neuropathy using corneal confocal microscopy: a development and validation study.

Diabetologia Nov 12, 2019
AIMS/HYPOTHESIS: Corneal confocal microscopy is a rapid non-invasive ophthalmic imaging technique that identifies peripheral and central neurodegenerative disease. Quantification of corneal sub-basal nerve plexus morphology, however, requires either ...
Algorithms Cornea Deep Learning Microscopy, Confocal Diabetes Mellitus, Type 1 Neurodegenerative Diseases Humans Artificial Intelligence Nerve Fibers Diabetic Neuropathies
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Forecasting Retinal Nerve Fiber Layer Thickness from Multimodal Temporal Data Incorporating OCT Volumes.

Ophthalmology. Glaucoma Nov 8, 2019
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.
Male Aged Optic Disk Humans Middle Aged Aged, 80 and over Retinal Ganglion Cells Glaucoma Follow-Up Studies Young Adult Visual Fields Forecasting Tomography, Optical Coherence Adult Retrospective Studies Nerve Fibers Intraocular Pressure Female
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Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness Maps.

Ophthalmology Sep 30, 2019
PURPOSE: To develop and evaluate a deep learning system for differentiating between eyes with and without glaucomatous visual field damage (GVFD) and predicting the severity of GFVD from spectral domain OCT (SD OCT) optic nerve head images.
Humans Glaucoma Female Aged Adult Male Diagnostic Techniques, Ophthalmological Optic Disk Middle Aged Retinal Ganglion Cells Deep Learning Visual Fields Vision Disorders Visual Field Tests Predictive Value of Tests Optic Nerve Diseases Nerve Fibers
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Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs.

Ophthalmology Sep 24, 2019
PURPOSE: To develop and validate a deep learning (DL) algorithm that predicts referable glaucomatous optic neuropathy (GON) and optic nerve head (ONH) features from color fundus images, to determine the relative importance of these features in referr...
Optic Nerve Diseases Ophthalmologists Glaucoma, Open-Angle Specialization Referral and Consultation Datasets as Topic Nerve Fibers Optic Disk Retinal Ganglion Cells Humans Retrospective Studies Female Aged Deep Learning ROC Curve Area Under Curve Sensitivity and Specificity Male Middle Aged
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Machine Learning Models for Diagnosing Glaucoma from Retinal Nerve Fiber Layer Thickness Maps.

Ophthalmology. Glaucoma Aug 23, 2019
PURPOSE: To assess the diagnostic accuracy of multiple machine learning models using full retinal nerve fiber layer (RNFL) thickness maps in detecting glaucoma.
Nerve Fibers Optic Disk Retinal Ganglion Cells Visual Fields Aged Intraocular Pressure Male Case-Control Studies Tomography, Optical Coherence Humans Glaucoma Machine Learning Female
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Accuracy of machine learning for differentiation between optic neuropathies and pseudopapilledema.

BMC ophthalmology Aug 9, 2019
BACKGROUND: This study is to evaluate the accuracy of machine learning for differentiation between optic neuropathies, pseudopapilledema (PPE) and normals.
Optic Neuritis Humans Nerve Fibers Machine Learning Reproducibility of Results Optic Disk ROC Curve Retinal Ganglion Cells Visual Acuity Optic Nerve Diseases Diagnosis, Differential Eye Diseases, Hereditary Tomography, Optical Coherence
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3D Neuron Reconstruction in Tangled Neuronal Image With Deep Networks.

IEEE transactions on medical imaging Jul 9, 2019
Digital reconstruction or tracing of 3D neuron is essential for understanding the brain functions. While existing automatic tracing algorithms work well for the clean neuronal image with a single neuron, they are not robust to trace the neuron surrou...
Neurons Microscopy Nerve Fibers Humans Algorithms Brain Animals Deep Learning Imaging, Three-Dimensional Mice
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