Retina fundus disease gray scale image perception using semantic segmentation model.

Ocular fundus illnesses such as diabetic retinopathy Retina Fundus Disease Gray Scale Image Perception using Semantic Segmentation Model, age-related macular degeneration, glaucoma, retinal detachment, and fundus tumors impact millions of individuals worldwide. Without correct diagnosis and proper treatment, these fundus diseases can cause irreversible vision loss or even blindness. Due to the varied thickness and diameter of retinal blood vessels, manual vessel segmentation is always challenging in a retinal image. Any sort of retinal illness must now undergo retinal blood vessel segmentation. The segmentation of retinal blood vessels is thought to be a useful method for making these diagnoses. By utilizing network topologies such as semantic pixel-wise segmentation (SegNet) and U-net, we hope to address the issues of substantial segmentation mistakes of the eyes. Accurate retinal blood vessel segmentation in Ocular fundus illnesses, which afflict millions of people worldwide, is very difficult to detect without the aid of the fundus. [ABSTRACT FROM AUTHOR]