Convolutional Neural Network Assessment to Identify Glaucoma in Eyes Using Retinal Fundus Images
摘要
In order to identify glaucoma, this study suggests an image processing technique using a computer tool. Glaucoma has been identified as one of the major factors that contribute to visual impairment, although early study on the condition was challenging. It is one of the causes of permanent visual impairment in people older than 40 years old. Because it balances convey ability, size, and cost, fundus imaging is a very popular screening method for glaucoma expose. We discuss improvements to disc segmentation alongside other studies in the literature. These upgrades include a novel technique for dividing the container at the threshold and a new comparison between the cup's and the disk's sizes. Results were obtained from a number of fundus photographs.