AIMC Topic: Fundus Oculi

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Predicting systemic diseases in fundus images: systematic review of setting, reporting, bias, and models' clinical availability in deep learning studies.

Eye (London, England) Jan 18, 2024
BACKGROUND: Analyzing fundus images with deep learning techniques is promising for screening systematic diseases. However, the quality of the rapidly increasing number of studies was variable and lacked systematic evaluation.
Fundus Oculi Retinal Diseases Humans Deep Learning
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The BONSAI (Brain and Optic Nerve Study with Artificial Intelligence) deep learning system can accurately identify pediatric papilledema on standard ocular fundus photographs.

Journal of AAPOS : the official publication of the American Association for Pediatric Ophthalmology and Strabismus Jan 10, 2024
BACKGROUND: Pediatric papilledema often reflects an underlying severe neurologic disorder and may be difficult to appreciate, especially in young children. Ocular fundus photographs are easy to obtain even in young children and in nonophthalmology se...
Fundus Oculi Papilledema Child Optic Nerve Artificial Intelligence Brain Deep Learning Child, Preschool Adult Humans
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AIROGS: Artificial Intelligence for Robust Glaucoma Screening Challenge.

IEEE transactions on medical imaging Jan 2, 2024
The early detection of glaucoma is essential in preventing visual impairment. Artificial intelligence (AI) can be used to analyze color fundus photographs (CFPs) in a cost-effective manner, making glaucoma screening more accessible. While AI models f...
Humans Algorithms Fundus Oculi Diagnostic Techniques, Ophthalmological Glaucoma Artificial Intelligence
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DeepGraFT: A novel semantic segmentation auxiliary ROI-based deep learning framework for effective fundus tessellation classification.

Computers in biology and medicine Dec 23, 2023
Fundus tessellation (FT) is a prevalent clinical feature associated with myopia and has implications in the development of myopic maculopathy, which causes irreversible visual impairment. Accurate classification of FT in color fundus photo can help p...
Humans Deep Learning Machine Learning Fundus Oculi Algorithms Semantics
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Suitability of machine learning for atrophy and fibrosis development in neovascular age-related macular degeneration.

Acta ophthalmologica Dec 22, 2023
PURPOSE: To assess the suitability of machine learning (ML) techniques in predicting the development of fibrosis and atrophy in patients with neovascular age-related macular degeneration (nAMD), receiving anti-VEGF treatment over a 36-month period.
Aged Aged, 80 and over Angiogenesis Inhibitors Intravitreal Injections Follow-Up Studies Fluorescein Angiography Retrospective Studies Male Humans Wet Macular Degeneration Female Atrophy Machine Learning Ranibizumab Fundus Oculi Vascular Endothelial Growth Factor A Visual Acuity Tomography, Optical Coherence Fibrosis
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A Deep Learning Model for Detecting Rhegmatogenous Retinal Detachment Using Ophthalmologic Ultrasound Images.

Ophthalmologica. Journal international d'ophtalmologie. International journal of ophthalmology. Zeitschrift fur Augenheilkunde Dec 19, 2023
INTRODUCTION: Rhegmatogenous retinal detachment (RRD) is one of the most common fundus diseases. Many rural areas of China have few ophthalmologists, and ophthalmologic ultrasound examination is of great significance for remote diagnosis of RRD. Ther...
Fundus Oculi Retinal Detachment Deep Learning Humans ROC Curve Neural Networks, Computer
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Quality assessment of colour fundus and fluorescein angiography images using deep learning.

The British journal of ophthalmology Dec 18, 2023
BACKGROUND/AIMS: Image quality assessment (IQA) is crucial for both reading centres in clinical studies and routine practice, as only adequate quality allows clinicians to correctly identify diseases and treat patients accordingly. Here we aim to dev...
Humans Color Fundus Oculi Fluorescein Angiography Neural Networks, Computer Deep Learning
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Explainable artificial intelligence for the automated assessment of the retinal vascular tortuosity.

Medical & biological engineering & computing Dec 7, 2023
Retinal vascular tortuosity is an excessive bending and twisting of the blood vessels in the retina that is associated with numerous health conditions. We propose a novel methodology for the automated assessment of the retinal vascular tortuosity fro...
Retinal Diseases Retinal Vessels Fundus Oculi Retina Artificial Intelligence Algorithms Humans
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Efficient feature selection based novel clinical decision support system for glaucoma prediction from retinal fundus images.

Medical engineering & physics Dec 7, 2023
The process of feature selection (FS) is vital aspect of machine learning (ML) model's performance enhancement where the objective is the selection of the most influential subset of features. This paper suggests the Gravitational search optimization ...
Decision Support Systems, Clinical Fundus Oculi Machine Learning Humans Algorithms Glaucoma
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Automatic interpretation and clinical evaluation for fundus fluorescein angiography images of diabetic retinopathy patients by deep learning.

The British journal of ophthalmology Nov 22, 2023
BACKGROUND/AIMS: Fundus fluorescein angiography (FFA) is an important technique to evaluate diabetic retinopathy (DR) and other retinal diseases. The interpretation of FFA images is complex and time-consuming, and the ability of diagnosis is uneven a...
Fundus Oculi Diabetic Retinopathy Deep Learning Fluorescein Angiography Neural Networks, Computer Diabetes Mellitus Humans
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