Color Fundus Photography and Deep Learning Applications in Alzheimer Disease.

Objective: To report the development and performance of 2 distinct deep learning models trained exclusively on retinal color fundus photographs to classify Alzheimer disease (AD).

Patients And Methods: Two independent datasets (UK Biobank and our tertiary academic institution) of good-quality retinal photographs derived from patients with AD and controls were used to build 2 deep learning models, between April 1, 2021, and January 30, 2024. ADVAS is a U-Net-based architecture that uses retinal vessel segmentation.

Thrombolytic Therapy for Central Retinal Artery Occlusion in an Academic Multi-Site Stroke Centre.

Central retinal artery occlusion (CRAO) is a subtype of acute ischaemic stroke leading to severe visual loss. A recent American Heart Association scientific statement proposed time-windows for thrombolysis in CRAO similar to acute ischaemic cerebral strokes. We aimed to review our academic multi-site stroke centre experience with intravenous (IVT) and intra-arterial thrombolysis (IAT) in CRAO between 1997 and 2022.

OTRE: Where Optimal Transport Guided Unpaired Image-to-Image Translation Meets Regularization by Enhancing.

Non-mydriatic retinal color fundus photography (CFP) is widely available due to the advantage of not requiring pupillary dilation, however, is prone to poor quality due to operators, systemic imperfections, or patient-related causes. Optimal retinal image quality is mandated for accurate medical diagnoses and automated analyses. Herein, we leveraged the theory to propose an unpaired image-to-image translation scheme for mapping low-quality retinal CFPs to high-quality counterparts.