AIMC Topic: Fundus Oculi
Clear Filters Showing 141 to 150 of 491 articles
A deep learning-based framework for retinal fundus image enhancement.
PloS one
Mar 16, 2023
PROBLEM: Low-quality fundus images with complex degredation can cause costly re-examinations of patients or inaccurate clinical diagnosis.
Sex determination using color fundus parameters in older adults of Kumejima population study.
Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
Mar 1, 2023
PURPOSE: Deep learning artificial intelligence can determine the sex using only fundus photographs. However, the factors used by deep learning to determine the sex are not visible. Therefore, the purpose of the study was to determine whether the sex ...
Application of Artificial Intelligence to Quantitative Assessment of Fundus Tessellated Density in Young Adults with Different Refractions.
Ophthalmic research
Feb 28, 2023
INTRODUCTION: The aim of this study was to quantitatively assess fundus tessellated density (FTD) and associated factors by artificial intelligence (AI) in young adults.
Automatic Detection of Peripheral Retinal Lesions From Ultrawide-Field Fundus Images Using Deep Learning.
Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
Feb 20, 2023
PURPOSE: To establish a multilabel-based deep learning (DL) algorithm for automatic detection and categorization of clinically significant peripheral retinal lesions using ultrawide-field fundus images.
Automatic vessel crossing and bifurcation detection based on multi-attention network vessel segmentation and directed graph search.
Computers in biology and medicine
Feb 15, 2023
Analysis of the vascular tree is the basic premise to automatically diagnose retinal biomarkers associated with ophthalmic and systemic diseases, among which accurate identification of intersection and bifurcation points is quite challenging but impo...
Deep Learning-based Prediction of Axial Length Using Ultra-widefield Fundus Photography.
Korean journal of ophthalmology : KJO
Feb 9, 2023
PURPOSE: To develop a deep learning model that can predict the axial lengths of eyes using ultra-widefield (UWF) fundus photography.
Accuracy and Time Comparison Between Side-by-Side and Artificial Intelligence Overlayed Images.
Ophthalmic surgery, lasers & imaging retina
Feb 1, 2023
BACKGROUND AND OBJECTIVE: The purpose of this study was to evaluate the accuracy and the time to find a lesion, taken in different platforms, color fundus photographs and infrared scanning laser ophthalmoscope images, using the traditional side-by-si...
Deep learning-based hemorrhage detection for diabetic retinopathy screening.
Scientific reports
Jan 27, 2023
Diabetic retinopathy is a retinal compilation that causes visual impairment. Hemorrhage is one of the pathological symptoms of diabetic retinopathy that emerges during disease development. Therefore, hemorrhage detection reveals the presence of diabe...
Developing a Novel Methodology by Integrating Deep Learning and HMM for Segmentation of Retinal Blood Vessels in Fundus Images.
Interdisciplinary sciences, computational life sciences
Jan 7, 2023
Accurate segregation of retinal blood vessels network plays a crucial role in clinical assessments, treatments, and rehabilitation process. Owing to the presence of acquisition and instrumentation anomalies, precise tracking of vessels network is cha...
A deep network embedded with rough fuzzy discretization for OCT fundus image segmentation.
Scientific reports
Jan 6, 2023
The noise and redundant information are the main reasons for the performance bottleneck of medical image segmentation algorithms based on the deep learning. To this end, we propose a deep network embedded with rough fuzzy discretization (RFDDN) for O...
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