AIMC Topic: Diagnostic Techniques, Ophthalmological
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Spatially Aware Dense-LinkNet Based Regression Improves Fluorescent Cell Detection in Adaptive Optics Ophthalmic Images.
IEEE journal of biomedical and health informatics
Dec 4, 2020
Retinal pigment epithelial (RPE) cells play an important role in nourishing retinal neurosensory photoreceptor cells, and numerous blinding diseases are associated with RPE defects. Their fluorescence signature can now be visualized in the living hum...
Hard Attention Net for Automatic Retinal Vessel Segmentation.
IEEE journal of biomedical and health informatics
Dec 4, 2020
Automated retinal vessel segmentation is among the most significant application and research topics in ophthalmologic image analysis. Deep learning based retinal vessel segmentation models have attracted much attention in the recent years. However, c...
ELEMENT: Multi-Modal Retinal Vessel Segmentation Based on a Coupled Region Growing and Machine Learning Approach.
IEEE journal of biomedical and health informatics
Dec 4, 2020
Vascular structures in the retina contain important information for the detection and analysis of ocular diseases, including age-related macular degeneration, diabetic retinopathy and glaucoma. Commonly used modalities in diagnosis of these diseases ...
Identifying Mouse Autoimmune Uveitis from Fundus Photographs Using Deep Learning.
Translational vision science & technology
Dec 2, 2020
PURPOSE: To develop a deep learning model for objective evaluation of experimental autoimmune uveitis (EAU), the animal model of posterior uveitis that reveals its essential pathological features via fundus photographs.
Predicting the risk of developing diabetic retinopathy using deep learning.
The Lancet. Digital health
Nov 26, 2020
BACKGROUND: Diabetic retinopathy screening is instrumental to preventing blindness, but scaling up screening is challenging because of the increasing number of patients with all forms of diabetes. We aimed to create a deep-learning system to predict ...
Deep learning classification of early normal-tension glaucoma and glaucoma suspects using Bruch's membrane opening-minimum rim width and RNFL.
Scientific reports
Nov 4, 2020
We aimed to classify early normal-tension glaucoma (NTG) and glaucoma suspect (GS) using Bruch's membrane opening-minimum rim width (BMO-MRW), peripapillary retinal nerve fiber layer (RNFL), and the color classification of RNFL based on a deep-learni...
Deep learning can generate traditional retinal fundus photographs using ultra-widefield images via generative adversarial networks.
Computer methods and programs in biomedicine
Sep 16, 2020
BACKGROUND AND OBJECTIVE: Retinal imaging has two major modalities, traditional fundus photography (TFP) and ultra-widefield fundus photography (UWFP). This study demonstrates the feasibility of a state-of-the-art deep learning-based domain transfer ...
Optic Disc Classification by Deep Learning versus Expert Neuro-Ophthalmologists.
Annals of neurology
Aug 7, 2020
OBJECTIVE: To compare the diagnostic performance of an artificial intelligence deep learning system with that of expert neuro-ophthalmologists in classifying optic disc appearance.
Economic Challenges of Artificial Intelligence Adoption for Diabetic Retinopathy.
Ophthalmology
Jul 25, 2020
A Review of Deep Learning for Screening, Diagnosis, and Detection of Glaucoma Progression.
Translational vision science & technology
Jul 22, 2020
UNLABELLED: Because of recent advances in computing technology and the availability of large datasets, deep learning has risen to the forefront of artificial intelligence, with performances that often equal, or sometimes even exceed, those of human s...
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