AIMC Topic: Macular Edema
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Integration of Optical Coherence Tomography Images and Real-Life Clinical Data for Deep Learning Modeling: A Unified Approach in Prognostication of Diabetic Macular Edema.
Journal of biophotonics
Dec 29, 2024
The primary ocular effect of diabetes is diabetic retinopathy (DR), which is associated with diabetic microangiopathy. Diabetic macular edema (DME) can cause vision loss for people with DR. For this reason, deciding on the appropriate treatment and f...
Self-supervised based clustering for retinal optical coherence tomography images.
Eye (London, England)
Oct 28, 2024
BACKGROUND: In response to the inadequacy of manual analysis in meeting the rising demand for retinal optical coherence tomography (OCT) images, a self-supervised learning-based clustering model was implemented.
Detection of Macular Neovascularization in Eyes Presenting with Macular Edema using OCT Angiography and a Deep Learning Model.
Ophthalmology. Retina
Oct 24, 2024
PURPOSE: To test the diagnostic performance of an artificial intelligence algorithm for detecting and segmenting macular neovascularization (MNV) with OCT and OCT angiography (OCTA) in eyes with macular edema from various diagnoses.
Prospective Studies
Female
Aged
Aged, 80 and over
Humans
Diabetic Retinopathy
Algorithms
Deep Learning
Macular Edema
Visual Acuity
Retinal Neovascularization
Fluorescein Angiography
Tomography, Optical Coherence
Retinal Vein Occlusion
Macula Lutea
Fundus Oculi
Cross-Sectional Studies
Male
Middle Aged
Novel artificial intelligence for diabetic retinopathy and diabetic macular edema: what is new in 2024?
Current opinion in ophthalmology
Sep 9, 2024
PURPOSE OF REVIEW: Given the increasing global burden of diabetic retinopathy and the rapid advancements in artificial intelligence, this review aims to summarize the current state of artificial intelligence technology in diabetic retinopathy detecti...
Artificial intelligence-based extraction of quantitative ultra-widefield fluorescein angiography parameters in retinal vein occlusion.
Canadian journal of ophthalmology. Journal canadien d'ophtalmologie
Aug 31, 2024
OBJECTIVE: To examine the association between quantitative vascular parameters extracted from intravenous fluorescein angiography (IVFA) and baseline clinical characteristics of patients with retinal vein occlusion (RVO).
Optimized deep CNN for detection and classification of diabetic retinopathy and diabetic macular edema.
BMC medical imaging
Aug 28, 2024
Diabetic Retinopathy (DR) and Diabetic Macular Edema (DME) are vision related complications prominently found in diabetic patients. The early identification of DR/DME grades facilitates the devising of an appropriate treatment plan, which ultimately ...
Prediction of treatment outcome for branch retinal vein occlusion using convolutional neural network-based retinal fluorescein angiography.
Scientific reports
Aug 28, 2024
Deep learning techniques were used in ophthalmology to develop artificial intelligence (AI) models for predicting the short-term effectiveness of anti-VEGF therapy in patients with macular edema secondary to branch retinal vein occlusion (BRVO-ME). 1...
A novel approach for automatic classification of macular degeneration OCT images.
Scientific reports
Aug 20, 2024
Age-related macular degeneration (AMD) and diabetic macular edema (DME) are significant causes of blindness worldwide. The prevalence of these diseases is steadily increasing due to population aging. Therefore, early diagnosis and prevention are cruc...
Hybrid deep learning models for the screening of Diabetic Macular Edema in optical coherence tomography volumes.
Scientific reports
Jul 31, 2024
Several studies published so far used highly selective image datasets from unclear sources to train computer vision models and that may lead to overestimated results, while those studies conducted in real-life remain scarce. To avoid image selection ...
A deep learning approach to hard exudates detection and disorganization of retinal inner layers identification on OCT images.
Scientific reports
Jul 19, 2024
The purpose of the study was to detect Hard Exudates (HE) and classify Disorganization of Retinal Inner Layers (DRIL) implementing a Deep Learning (DL) system on optical coherence tomography (OCT) images of eyes with diabetic macular edema (DME). We ...
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