AIMC Topic: Fundus Oculi
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Detection of exudates in fundus photographs using deep neural networks and anatomical landmark detection fusion.
Computer methods and programs in biomedicine
Oct 6, 2016
BACKGROUND AND OBJECTIVE: Diabetic retinopathy is one of the leading disabling chronic diseases and one of the leading causes of preventable blindness in developed world. Early diagnosis of diabetic retinopathy enables timely treatment and in order t...
Retinal vessel segmentation in colour fundus images using Extreme Learning Machine.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
May 30, 2016
Attributes of the retinal vessel play important role in systemic conditions and ophthalmic diagnosis. In this paper, a supervised method based on Extreme Learning Machine (ELM) is proposed to segment retinal vessel. Firstly, a set of 39-D discriminat...
Fast Convolutional Neural Network Training Using Selective Data Sampling: Application to Hemorrhage Detection in Color Fundus Images.
IEEE transactions on medical imaging
Feb 8, 2016
Convolutional neural networks (CNNs) are deep learning network architectures that have pushed forward the state-of-the-art in a range of computer vision applications and are increasingly popular in medical image analysis. However, training of CNNs is...
A Hybrid Swarm Algorithm for optimizing glaucoma diagnosis.
Computers in biology and medicine
Jun 10, 2015
Glaucoma is among the most common causes of permanent blindness in human. Because the initial symptoms are not evident, mass screening would assist early diagnosis in the vast population. Such mass screening requires an automated diagnosis technique....
Fundus Refraction Offset as a Personalized Biomarker for 12-Year Risk of Retinal Detachment.
Investigative ophthalmology & visual science
Jul 1, 2025
PURPOSE: The purpose of this study was to investigate the potential of a novel anatomical metric of ametropia-fundus refraction offset (FRO)-in stratifying the risk of retinal detachment (RD) or breaks, beyond the influence of risk factors including ...
Current and future directions for the use of handheld fundus cameras in telehealth.
Expert review of medical devices
Jul 1, 2025
INTRODUCTION: A shortage of trained retinal specialists has created a growing need for a telehealth retinal screening alternative. Recent developments in handheld fundus cameras, enhanced by artificial intelligence (AI) and machine learning (ML) meth...
AI Quantification of Vascular Lesions in Mouse Fundus Fluorescein Angiography.
Translational vision science & technology
Jun 2, 2025
PURPOSE: Quantifying vascular leakage in fundus fluorescein angiography (FFA) is a critical endpoint in preclinical models of diseases such as neovascular age-related macular degeneration, retinopathy of prematurity, and diabetic retinopathy. Traditi...
Optimised Hybrid Attention-Based Capsule Network Integrated Three-Pathway Network for Chronic Disease Detection in Retinal Images.
Journal of evaluation in clinical practice
Jun 1, 2025
BACKGROUND: Over the past 20 years, researchers have concentrated on generating retinal images as a means of detecting and classifying chronic diseases. Early diagnosis and treatment are essential to avoid chronic diseases. Manually grading retinal i...
Joint high-resolution feature learning and vessel-shape aware convolutions for efficient vessel segmentation.
Computers in biology and medicine
Jun 1, 2025
Clear imagery of retinal vessels is one of the critical shreds of evidence in specific disease diagnosis and evaluation, including sophisticated hierarchical topology and plentiful-and-intensive capillaries. In this work, we propose a new topology- a...
GENERATIVE DEEP LEARNING APPROACH TO PREDICT POSTTREATMENT OPTICAL COHERENCE TOMOGRAPHY IMAGES OF AGE-RELATED MACULAR DEGENERATION AFTER 12 MONTHS.
Retina (Philadelphia, Pa.)
Jun 1, 2025
PURPOSE: Predicting long-term anatomical responses in neovascular age-related macular degeneration patients is critical for patient-specific management. This study validates a generative deep learning model to predict 12-month posttreatment optical c...
Time Factors
Angiogenesis Inhibitors
Follow-Up Studies
Aged, 80 and over
Male
Deep Learning
Vascular Endothelial Growth Factor A
Intravitreal Injections
Fluorescein Angiography
Visual Acuity
Tomography, Optical Coherence
Fundus Oculi
Humans
Retrospective Studies
Female
Aged
Macula Lutea
Ranibizumab
Wet Macular Degeneration
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