AIMC Topic: Fundus Oculi
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Robust semi-automatic vessel tracing in the human retinal image by an instance segmentation neural network.
Science advances
Apr 4, 2025
Vasculature morphology and hierarchy are essential for blood perfusion. Human retinal circulation is an intricate vascular system emerging and remerging at the optic nerve head (ONH). Tracing retinal vascular branching from ONH can allow detailed mor...
Label-Aware Dual Graph Neural Networks for Multi-Label Fundus Image Classification.
IEEE journal of biomedical and health informatics
Apr 4, 2025
Fundus disease is a complex and universal disease involving a variety of pathologies. Its early diagnosis using fundus images can effectively prevent further diseases and provide targeted treatment plans for patients. Recent deep learning models for ...
Hybrid deep learning framework for diabetic retinopathy classification with optimized attention AlexNet.
Computers in biology and medicine
Mar 27, 2025
Diabetic retinopathy (DR) is a chronic condition associated with diabetes that can lead to vision impairment and, if not addressed, may progress to irreversible blindness. Consequently, it is essential to detect pathological changes in the retina to ...
Addressing underestimation and explanation of retinal fundus photo-based cardiovascular disease risk score: Algorithm development and validation.
Computers in biology and medicine
Mar 9, 2025
OBJECTIVE: To resolve the underestimation problem and investigate the mechanism of the AI model which employed to predict cardiovascular disease (CVD) risk scores from retinal fundus photos.
Retinal vein occlusion risk prediction without fundus examination using a no-code machine learning tool for tabular data: a nationwide cross-sectional study from South Korea.
BMC medical informatics and decision making
Mar 7, 2025
BACKGROUND: Retinal vein occlusion (RVO) is a leading cause of vision loss globally. Routine health check-up data-including demographic information, medical history, and laboratory test results-are commonly utilized in clinical settings for disease r...
UGS-M3F: unified gated swin transformer with multi-feature fully fusion for retinal blood vessel segmentation.
BMC medical imaging
Mar 6, 2025
Automated segmentation of retinal blood vessels in fundus images plays a key role in providing ophthalmologists with critical insights for the non-invasive diagnosis of common eye diseases. Early and precise detection of these conditions is essential...
D-GET: Group-Enhanced Transformer for Diabetic Retinopathy Severity Classification in Fundus Fluorescein Angiography.
Journal of medical systems
Mar 6, 2025
Early detection of Diabetic Retinopathy (DR) is vital for preserving vision and preventing deterioration of eyesight. Fundus Fluorescein Angiography (FFA), recognized as the gold standard for diagnosing DR, effectively reveals abnormalities in retina...
MSTNet: Multi-scale spatial-aware transformer with multi-instance learning for diabetic retinopathy classification.
Medical image analysis
Feb 24, 2025
Diabetic retinopathy (DR), the leading cause of vision loss among diabetic adults worldwide, underscores the importance of early detection and timely treatment using fundus images to prevent vision loss. However, existing deep learning methods strugg...
Capsule network-based deep learning for early and accurate diabetic retinopathy detection.
International ophthalmology
Feb 18, 2025
Glaucoma, an optic nerve disease resulting in blindness if left untreated, is a difficult condition in healthcare in view of its diagnostic difficulties. Past approaches are based on assessment of the fundus images and the size of the cup and the dis...
Gabor-modulated depth separable convolution for retinal vessel segmentation in fundus images.
Computers in biology and medicine
Feb 12, 2025
BACKGROUND: In diabetic retinopathy, precise segmentation of retinal vessels is essential for accurate diagnosis and effective disease management. This task is particularly challenging due to the varying sizes of vessels, their bifurcations, and the ...
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