AIMC Topic: Fluorescein Angiography

Clear Filters Showing 101 to 110 of 150 articles

Validation of a Deep Learning Model to Screen for Glaucoma Using Images from Different Fundus Cameras and Data Augmentation.

Ophthalmology. Glaucoma Apr 1, 2019
PURPOSE: To validate a deep residual learning algorithm to diagnose glaucoma from fundus photography using different fundus cameras at different institutes.
Humans Glaucoma Algorithms Deep Learning ROC Curve Fundus Oculi Optic Disk Fluorescein Angiography Female Aged Cross-Sectional Studies Male
View on PubMed DOI

Deep learning-based detection and classification of geographic atrophy using a deep convolutional neural network classifier.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie Aug 8, 2018
PURPOSE: To automatically detect and classify geographic atrophy (GA) in fundus autofluorescence (FAF) images using a deep learning algorithm.
Fluorescein Angiography Machine Learning Geographic Atrophy Algorithms Female Reproducibility of Results Diagnosis, Computer-Assisted Tomography, Optical Coherence Aged Humans Fundus Oculi Sensitivity and Specificity Neural Networks, Computer Healthy Volunteers Male Middle Aged Disease Progression
View on PubMed DOI

Deep Convolutional Neural Network-Based Early Automated Detection of Diabetic Retinopathy Using Fundus Image.

Molecules (Basel, Switzerland) Nov 23, 2017
The automatic detection of diabetic retinopathy is of vital importance, as it is the main cause of irreversible vision loss in the working-age population in the developed world. The early detection of diabetic retinopathy occurrence can be very helpf...
Humans Fundus Oculi Retina Fluorescein Angiography Diabetic Retinopathy Neural Networks, Computer Algorithms Image Processing, Computer-Assisted
View on PubMed DOI

Use of a Neural Net to Model the Impact of Optical Coherence Tomography Abnormalities on Vision in Age-related Macular Degeneration.

American journal of ophthalmology Oct 31, 2017
PURPOSE: To develop a neural network for the estimation of visual acuity from optical coherence tomography (OCT) images of patients with neovascular age-related macular degeneration (AMD) and to demonstrate its use to model the impact of specific con...
Neural Networks, Computer Retrospective Studies Female Reproducibility of Results Aged Humans Fundus Oculi Fluorescein Angiography Macula Lutea Wet Macular Degeneration Male Middle Aged Visual Acuity Tomography, Optical Coherence
View on PubMed DOI

Pneumatic Displacement of Submacular Hemorrhage with Subretinal Air and Tissue Plasminogen Activator: Initial United States Experience.

Ophthalmology. Retina Sep 28, 2017
PURPOSE: To present the initial multicenter experience of using subretinal air injection in combination with tissue plasminogen activator (tPA) at the time of pars plana vitrectomy (PPV) to displace submacular hemorrhage (SMH).
Retinal Hemorrhage Vitrectomy Air Endotamponade Fluorescein Angiography Injections, Intraocular United States Treatment Outcome Aged, 80 and over Follow-Up Studies Male Fibrinolytic Agents Visual Acuity Middle Aged Tomography, Optical Coherence Time Factors Humans Fundus Oculi Retrospective Studies Retina Female Tissue Plasminogen Activator Aged
View on PubMed DOI

Non-proliferative diabetic retinopathy symptoms detection and classification using neural network.

Journal of medical engineering & technology Aug 8, 2017
Diabetic retinopathy (DR) causes blindness in the working age for people with diabetes in most countries. The increasing number of people with diabetes worldwide suggests that DR will continue to be major contributors to vision loss. Early detection ...
Pattern Recognition, Automated Fluorescein Angiography Symptom Assessment Female Reproducibility of Results Aged Sensitivity and Specificity Male Middle Aged Disease Progression Decision Support Systems, Clinical Image Interpretation, Computer-Assisted Humans Diabetic Retinopathy Neural Networks, Computer
View on PubMed DOI

Machine Learning to Analyze the Prognostic Value of Current Imaging Biomarkers in Neovascular Age-Related Macular Degeneration.

Ophthalmology. Retina May 31, 2017
PURPOSE: To evaluate the potential of machine learning to predict best-corrected visual acuity (BCVA) outcomes from structural and functional assessments during the initiation phase in patients receiving standardized ranibizumab therapy for neovascul...
Humans Machine Learning Vascular Endothelial Growth Factor A Intravitreal Injections Fluorescein Angiography Macula Lutea Ranibizumab Retinal Pigment Epithelium Wet Macular Degeneration Treatment Outcome Follow-Up Studies Visual Acuity Tomography, Optical Coherence Fundus Oculi Prospective Studies Prognosis Reproducibility of Results Angiogenesis Inhibitors
View on PubMed DOI

Multimodal Imaging in Diabetic Macular Edema.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.) Jan 29, 2017
Throughout ophthalmic history it has been shown that progress has gone hand in hand with technological breakthroughs. In the past, fluorescein angiography and fundus photographs were the most commonly used imaging modalities in the management of diab...
Humans Diabetic Retinopathy Multimodal Imaging Fluorescein Angiography Ophthalmoscopy Optics and Photonics Tomography, Optical Coherence Macular Edema Optical Imaging Diagnostic Techniques, Ophthalmological
View on PubMed DOI

Comparing humans and deep learning performance for grading AMD: A study in using universal deep features and transfer learning for automated AMD analysis.

Computers in biology and medicine Jan 27, 2017
BACKGROUND: When left untreated, age-related macular degeneration (AMD) is the leading cause of vision loss in people over fifty in the US. Currently it is estimated that about eight million US individuals have the intermediate stage of AMD that is o...
Pattern Recognition, Automated Fluorescein Angiography Macular Degeneration Image Interpretation, Computer-Assisted Observer Variation Early Diagnosis Humans Machine Learning Algorithms Reproducibility of Results Sensitivity and Specificity Severity of Illness Index
View on PubMed DOI

A Discriminatively Trained Fully Connected Conditional Random Field Model for Blood Vessel Segmentation in Fundus Images.

IEEE transactions on bio-medical engineering Feb 26, 2016
GOAL: In this work, we present an extensive description and evaluation of our method for blood vessel segmentation in fundus images based on a discriminatively trained fully connected conditional random field model.
Photography Models, Cardiovascular Retinal Artery Image Interpretation, Computer-Assisted Pattern Recognition, Automated Computer Simulation Retinal Diseases Reproducibility of Results Fluorescein Angiography Sensitivity and Specificity Ophthalmoscopy Models, Statistical Humans Machine Learning
View on PubMed DOI
Popular Topics
Recent Journals