Retinal vessel segmentation is essential to the diagnosis and treatment of many ocular diseases; it is a critical task in the field of medical image analysis. The widely used U-Net architecture is combined with a Channel Attention Mechanism (CAM) to present a novel method of retinal vessel segmentation in this paper. The suggested technique creates a novel and incredibly successful approach by fusing the U-Net’s semantic segmentation strengths with the CAM’s capacity to concentrate on informative features.