AIMC Topic: Nerve Fibers

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

Studies in health technology and informatics Jun 26, 2020
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...
Nerve Fibers Neural Networks, Computer Image Processing, Computer-Assisted
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Automated Nerve Fibres Identification and Morphometry Analysis with Neural Network Based Tool in MATLAB.

Studies in health technology and informatics Jun 16, 2020
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...
Neural Networks, Computer Image Processing, Computer-Assisted Nerve Fibers
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Diagnosing Glaucoma With Spectral-Domain Optical Coherence Tomography Using Deep Learning Classifier.

Journal of glaucoma Apr 1, 2020
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...
Humans Glaucoma Female Aged Middle Aged Deep Learning ROC Curve Area Under Curve Adult Sensitivity and Specificity Intraocular Pressure Male Retinal Ganglion Cells Tomography, Optical Coherence Visual Fields Nerve Fibers Optic Disk
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Assessment of a Segmentation-Free Deep Learning Algorithm for Diagnosing Glaucoma From Optical Coherence Tomography Scans.

JAMA ophthalmology Apr 1, 2020
IMPORTANCE: Conventional segmentation of the retinal nerve fiber layer (RNFL) is prone to errors that may affect the accuracy of spectral-domain optical coherence tomography (SD-OCT) scans in detecting glaucomatous damage.
Retinal Ganglion Cells Visual Fields Visual Field Tests Glaucoma, Open-Angle Deep Learning ROC Curve Tomography, Optical Coherence Nerve Fibers Female Aged Gonioscopy Aged, 80 and over Slit Lamp Microscopy Adult Cross-Sectional Studies Intraocular Pressure Male Middle Aged Humans Algorithms
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Multiple-Image Deep Learning Analysis for Neuropathy Detection in Corneal Nerve Images.

Cornea Mar 1, 2020
PURPOSE: Automated classification of corneal confocal images from healthy subjects and diabetic subjects with neuropathy.
Nerve Fibers Diabetic Neuropathies Corneal Diseases Ophthalmic Nerve Algorithms Female Reproducibility of Results Cornea Male Middle Aged Deep Learning Microscopy, Confocal Humans
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Diagnosis of Glaucoma on Retinal Fundus Images Using Deep Learning: Detection of Nerve Fiber Layer Defect and Optic Disc Analysis.

Advances in experimental medicine and biology Jan 1, 2020
Early detection of glaucoma is important to slow down progression of the disease and to prevent total vision loss. Retinal fundus photography is frequently obtained for various eye disease diagnosis and record and is a suitable screening exam for its...
Fundus Oculi Humans Nerve Fibers Glaucoma Optic Disk Deep Learning
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Enhancing the Accuracy of Glaucoma Detection from OCT Probability Maps using Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
We describe and assess convolutional neural network (CNN) models for detection of glaucoma based upon optical coherence tomography (OCT) retinal nerve fiber layer (RNFL) probability maps. CNNs pretrained on natural images performed comparably to CNNs...
Humans Neural Networks, Computer Glaucoma ROC Curve Tomography, Optical Coherence Probability Nerve Fibers
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Screening Glaucoma With Red-free Fundus Photography Using Deep Learning Classifier and Polar Transformation.

Journal of glaucoma Mar 1, 2019
UNLABELLED: PRéCIS:: The novel proposed algorithm using deep learning classifier and polar transformation technique can be an economical as well as an effective tool for early detection of glaucomatous RNFL defect.
Retrospective Studies Female Adult Intraocular Pressure Male Middle Aged Deep Learning ROC Curve Glaucoma, Open-Angle Humans Retinal Ganglion Cells Area Under Curve Ophthalmologic Surgical Procedures Tomography, Optical Coherence Diagnostic Techniques, Ophthalmological Image Interpretation, Computer-Assisted Photography Nerve Fibers
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Macular Vessel Density and Ganglion Cell/Inner Plexiform Layer Thickness and Their Combinational Index Using Artificial Intelligence.

Journal of glaucoma Sep 1, 2018
PURPOSE: To evaluate the relationship between macular vessel density and ganglion cell to inner plexiform layer thickness (GCIPLT) and to compare their diagnostic performance. We attempted to develop a new combined parameter using an artificial neura...
Retinal Ganglion Cells Humans Retinal Vessels Neural Networks, Computer Glaucoma, Open-Angle Artificial Intelligence Female Area Under Curve Tomography, Optical Coherence Nerve Fibers Aged Adult Male Cross-Sectional Studies Middle Aged Intraocular Pressure Case-Control Studies ROC Curve
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Retinal Nerve Fiber Layer Features Identified by Unsupervised Machine Learning on Optical Coherence Tomography Scans Predict Glaucoma Progression.

Investigative ophthalmology & visual science Jun 1, 2018
PURPOSE: To apply computational techniques to wide-angle swept-source optical coherence tomography (SS-OCT) images to identify novel, glaucoma-related structural features and improve detection of glaucoma and prediction of future glaucomatous progres...
Visual Field Tests Optic Nerve Diseases Glaucoma, Open-Angle Middle Aged Tonometry, Ocular Aged Tomography, Optical Coherence Disease Progression Adult Nerve Fibers Humans Unsupervised Machine Learning Intraocular Pressure Optic Disk Retrospective Studies Principal Component Analysis Male Retinal Ganglion Cells Female
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