AIMC Topic: Macular Edema

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Reinforcement-based leveraging transfer learning for multiclass optical coherence tomography images classification.

Scientific reports
The accurate diagnosis of retinal diseases, such as Diabetic Macular Edema (DME) and Age-related Macular Degeneration (AMD), is essential for preventing vision loss. Optical Coherence Tomography (OCT) imaging plays a crucial role in identifying these...

Application of deep learning algorithm for judicious use of anti-VEGF in diabetic macular edema.

Scientific reports
Diabetic Macular Edema (DME) is a major complication of diabetic retinopathy characterized by fluid accumulation in the macula, leading to vision impairment. The standard treatment involves anti-VEGF (Vascular Endothelial Growth Factor) therapy, but ...

Estimating Visual Acuity With Spectacle Correction From Fundus Photos Using Artificial Intelligence.

JAMA network open
IMPORTANCE: Determining spectacle-corrected visual acuity (VA) is essential when managing many ophthalmic diseases. If artificial intelligence (AI) evaluations of macular images estimated this VA from a fundus image, AI might provide spectacle-correc...

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
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)
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.

Novel artificial intelligence for diabetic retinopathy and diabetic macular edema: what is new in 2024?

Current opinion in ophthalmology
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
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
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
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...