AIMC Topic: Fundus Oculi
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Deep learning in geographic atrophy: the best is yet to come.
The Lancet. Digital health
Sep 8, 2021
Ophthalmic Disease Detection via Deep Learning With a Novel Mixture Loss Function.
IEEE journal of biomedical and health informatics
Sep 3, 2021
With the popularization of computer-aided diagnosis (CAD) technologies, more and more deep learning methods are developed to facilitate the detection of ophthalmic diseases. In this article, the deep learning-based detections for some common eye dise...
EAD-Net: A Novel Lesion Segmentation Method in Diabetic Retinopathy Using Neural Networks.
Disease markers
Sep 1, 2021
Diabetic retinopathy (DR) is a common chronic fundus disease, which has four different kinds of microvessel structure and microvascular lesions: microaneurysms (MAs), hemorrhages (HEs), hard exudates, and soft exudates. Accurate detection and countin...
Deep learning algorithm using fundus photographs for 10-year risk assessment of ischemic cardiovascular diseases in China.
Science bulletin
Aug 28, 2021
Automatic detection of 39 fundus diseases and conditions in retinal photographs using deep neural networks.
Nature communications
Aug 10, 2021
Retinal fundus diseases can lead to irreversible visual impairment without timely diagnoses and appropriate treatments. Single disease-based deep learning algorithms had been developed for the detection of diabetic retinopathy, age-related macular de...
Neovascularization Detection and Localization in Fundus Images Using Deep Learning.
Sensors (Basel, Switzerland)
Aug 6, 2021
Proliferative Diabetic Retinopathy (PDR) is a severe retinal disease that threatens diabetic patients. It is characterized by neovascularization in the retina and the optic disk. PDR clinical features contain highly intense retinal neovascularization...
DeepUWF: An Automated Ultra-Wide-Field Fundus Screening System via Deep Learning.
IEEE journal of biomedical and health informatics
Aug 5, 2021
The emerging ultra-wide field of view (UWF) fundus color imaging is a powerful tool for fundus screening. However, manual screening is labor-intensive and subjective. Based on 2644 UWF images, a set of early fundus abnormal screening system named Dee...
Accuracy of automated machine learning in classifying retinal pathologies from ultra-widefield pseudocolour fundus images.
The British journal of ophthalmology
Aug 3, 2021
AIMS: Automated machine learning (AutoML) is a novel tool in artificial intelligence (AI). This study assessed the discriminative performance of AutoML in differentiating retinal vein occlusion (RVO), retinitis pigmentosa (RP) and retinal detachment ...
Automated detection of retinal exudates and drusen in ultra-widefield fundus images based on deep learning.
Eye (London, England)
Aug 3, 2021
BACKGROUND: Retinal exudates and/or drusen (RED) can be signs of many fundus diseases that can lead to irreversible vision loss. Early detection and treatment of these diseases are critical for improving vision prognosis. However, manual RED screenin...
Deep learning-assisted (automatic) diagnosis of glaucoma using a smartphone.
The British journal of ophthalmology
Jul 14, 2021
BACKGROUND/AIMS: To validate a deep learning algorithm to diagnose glaucoma from fundus photography obtained with a smartphone.
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