AIMC Topic: Fundus Oculi

Clear Filters Showing 31 to 40 of 491 articles

Classification of fundus autofluorescence images based on macular function in retinitis pigmentosa using convolutional neural networks.

Japanese journal of ophthalmology Feb 12, 2025
PURPOSE: To determine whether convolutional neural networks (CNN) can classify the severity of central vision loss using fundus autofluorescence (FAF) images and color fundus images of retinitis pigmentosa (RP), and to evaluate the utility of those i...
Macula Lutea Retinitis Pigmentosa Visual Acuity Tomography, Optical Coherence Fundus Oculi Visual Fields Fluorescein Angiography Middle Aged Convolutional Neural Networks Adolescent Adult Male Humans Neural Networks, Computer Retrospective Studies Female Aged Young Adult
View on PubMed DOI

A novel deep learning framework for retinal disease detection leveraging contextual and local features cues from retinal images.

Medical & biological engineering & computing Feb 7, 2025
Retinal diseases are a serious global threat to human vision, and early identification is essential for effective prevention and treatment. However, current diagnostic methods rely on manual analysis of fundus images, which heavily depends on the exp...
Humans Neural Networks, Computer Retina Algorithms Image Interpretation, Computer-Assisted Deep Learning Retinal Diseases Image Processing, Computer-Assisted Fundus Oculi
View on PubMed DOI

Rim learning framework based on TS-GAN: A new paradigm of automated glaucoma screening from fundus images.

Computers in biology and medicine Feb 3, 2025
Glaucoma detection from fundus images often relies on biomarkers such as the Cup-to-Disc Ratio (CDR) and Rim-to-Disc Ratio (RDR). However, precise segmentation of the optic cup and disc is challenging due to low-contrast boundaries and the interferen...
Humans Neural Networks, Computer Glaucoma Fundus Oculi Deep Learning Image Interpretation, Computer-Assisted Image Processing, Computer-Assisted Optic Disk
View on PubMed DOI

Fundus camera-based precision monitoring of blood vitamin A level for Wagyu cattle using deep learning.

Scientific reports Feb 3, 2025
In the wagyu industry worldwide, high-quality marbling beef is produced by promoting intramuscular fat deposition during cattle fattening stage through dietary vitamin A control. Thus, however, cattle become susceptible to either vitamin A deficiency...
Vitamin A Deficiency Photography Animals Deep Learning Cattle Cattle Diseases Fundus Oculi Vitamin A
View on PubMed DOI

Efficient diagnosis of retinal disorders using dual-branch semi-supervised learning (DB-SSL): An enhanced multi-class classification approach.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Feb 1, 2025
The early diagnosis of retinal disorders is essential in preventing permanent or partial blindness. Identifying these conditions promptly guarantees early treatment and prevents blindness. However, the challenge lies in accurately diagnosing these co...
Humans Neural Networks, Computer Fundus Oculi Supervised Machine Learning Image Interpretation, Computer-Assisted Retinal Diseases
View on PubMed DOI

Identification of diabetic retinopathy lesions in fundus images by integrating CNN and vision mamba models.

PloS one Jan 28, 2025
Diabetic retinopathy, a retinal disorder resulting from diabetes mellitus, is a prominent cause of visual degradation and loss among the global population. Therefore, the identification and classification of diabetic retinopathy are of utmost importa...
Image Processing, Computer-Assisted Neural Networks, Computer Humans Image Interpretation, Computer-Assisted Fundus Oculi Diabetic Retinopathy Algorithms Deep Learning
View on PubMed DOI

Multi scale multi attention network for blood vessel segmentation in fundus images.

Scientific reports Jan 27, 2025
Precise segmentation of retinal vasculature is crucial for the early detection, diagnosis, and treatment of vision-threatening ailments. However, this task is challenging due to limited contextual information, variations in vessel thicknesses, the co...
Image Processing, Computer-Assisted Fundus Oculi Retinal Vessels Algorithms ROC Curve Humans Neural Networks, Computer
View on PubMed DOI

Optimising deep learning models for ophthalmological disorder classification.

Scientific reports Jan 24, 2025
Fundus imaging, a technique for recording retinal structural components and anomalies, is essential for observing and identifying ophthalmological diseases. Disorders such as hypertension, glaucoma, and diabetic retinopathy are indicated by structura...
Fundus Oculi Eye Diseases Glaucoma Humans Databases, Factual Diabetic Retinopathy Deep Learning Neural Networks, Computer
View on PubMed DOI

DAU-Net: a novel U-Net with dual attention for retinal vessel segmentation.

Biomedical physics & engineering express Jan 22, 2025
In fundus images, precisely segmenting retinal blood vessels is important for diagnosing eye-related conditions, such as diabetic retinopathy and hypertensive retinopathy or other eye-related disorders. In this work, we propose an enhanced U-shaped n...
Algorithms Image Processing, Computer-Assisted Fundus Oculi Image Interpretation, Computer-Assisted Retinal Vessels Humans Diabetic Retinopathy Neural Networks, Computer
View on PubMed DOI

Deep learning generalization for diabetic retinopathy staging from fundus images.

Physiological measurement Jan 22, 2025
. Diabetic retinopathy (DR) is a serious diabetes complication that can lead to vision loss, making timely identification crucial. Existing data-driven algorithms for DR staging from digital fundus images (DFIs) often struggle with generalization due...
Deep Learning Image Processing, Computer-Assisted Humans Fundus Oculi Diabetic Retinopathy
View on PubMed DOI
Popular Topics
Recent Journals