Segmentation of Retinal Images using Transformer-based models

Retinal vessel segmentation is a crucial process in ophthalmology, aiding in the diagnosis and treatment of eye diseases like diabetic retinopathy and glaucoma. It involves extracting blood vessels from retinal images to analyze their structure and detect abnormalities. Advanced methods utilizing deep learning and image processing techniques enhance the accuracy and efficiency of segmentation. These methods capture fine details and variations in the retinal vasculature, leading to improved diagnostic outcomes and better patient care.