AIMC Topic: Fundus Oculi
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A MULTITASK DEEP-LEARNING SYSTEM FOR ASSESSMENT OF DIABETIC MACULAR ISCHEMIA ON OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY IMAGES.
Retina (Philadelphia, Pa.)
Jan 1, 2022
PURPOSE: We aimed to develop and test a deep-learning system to perform image quality and diabetic macular ischemia (DMI) assessment on optical coherence tomography angiography (OCTA) images.
Single-Examination Risk Prediction of Severe Retinopathy of Prematurity.
Pediatrics
Dec 1, 2021
BACKGROUND AND OBJECTIVES: Retinopathy of prematurity (ROP) is a leading cause of childhood blindness. Screening and treatment reduces this risk, but requires multiple examinations of infants, most of whom will not develop severe disease. Previous wo...
Improved Automatic Grading of Diabetic Retinopathy Using Deep Learning and Principal Component Analysis.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
Diabetic retinopathy (DR) is one of the most common chronic diseases around the world. Early screening and diagnosis of DR patients through retinal fundus is always preferred. However, image screening and diagnosis is a highly time-consuming task for...
Towards Stroke Biomarkers on Fundus Retinal Imaging: A Comparison Between Vasculature Embeddings and General Purpose 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
Nov 1, 2021
Fundus Retinal imaging is an easy-to-acquire modality typically used for monitoring eye health. Current evidence indicates that the retina, and its vasculature in particular, is associated with other disease processes making it an ideal candidate for...
An Efficient Deep Learning Network for Automatic Detection of Neovascularization in Color Fundus Images.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
Retinopathy screening is a non-invasive method to collect retinal images and neovascularization detection from retinal images plays a significant role on the identification and classification of diabetes retinopathy. In this paper, an efficient deep ...
Ocular Diseases Detection using Recent Deep Learning Techniques.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
Early fundus screening is a cost-effective and efficient approach to reduce ophthalmic disease-related blindness in ophthalmology. Manual evaluation is time-consuming. Ophthalmic disease detection studies have shown interesting results thanks to the ...
IMPACT OF RESIDUAL SUBRETINAL FLUID VOLUMES ON TREATMENT OUTCOMES IN A SUBRETINAL FLUID-TOLERANT TREAT-AND-EXTEND REGIMEN.
Retina (Philadelphia, Pa.)
Nov 1, 2021
PURPOSE: To investigate associations between residual subretinal fluid (rSRF) volumes, quantified using artificial intelligence and treatment outcomes in a subretinal fluid (SRF)-tolerant treat-and-extend (T&E) regimen in neovascular age-related macu...
Vascular Endothelial Growth Factor A
Intravitreal Injections
Fluorescein Angiography
Visual Acuity
Tomography, Optical Coherence
Fundus Oculi
Drug Tolerance
Ranibizumab
Wet Macular Degeneration
Subretinal Fluid
Humans
Artificial Intelligence
Prospective Studies
Angiogenesis Inhibitors
Treatment Outcome
Follow-Up Studies
Identification of glaucoma from fundus images using deep learning techniques.
Indian journal of ophthalmology
Oct 1, 2021
PURPOSE: Glaucoma is one of the preeminent causes of incurable visual disability and blindness across the world due to elevated intraocular pressure within the eyes. Accurate and timely diagnosis is essential for preventing visual disability. Manual ...
Quantitative Assessment of Fundus Tessellated Density and Associated Factors in Fundus Images Using Artificial Intelligence.
Translational vision science & technology
Aug 2, 2021
PURPOSE: This study aimed to quantitative assess the fundus tessellated density (FTD) and associated factors on the basis of fundus photographs using artificial intelligence.
Application of Comprehensive Artificial intelligence Retinal Expert (CARE) system: a national real-world evidence study.
The Lancet. Digital health
Aug 1, 2021
BACKGROUND: Medical artificial intelligence (AI) has entered the clinical implementation phase, although real-world performance of deep-learning systems (DLSs) for screening fundus disease remains unsatisfactory. Our study aimed to train a clinically...
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