GLAUCOMA DETECTION USING RETINAL IMAGE-AN AUTOMATED APPROACH FOR EARLY DIAGNOSIS
Uvan S S
Paper Contents
Abstract
optic nerve is harmed by which results in vision loss andultimately blindness. Vision loss may develop as a result of thesymptoms that may not be noticeable. Early therapy can to preventfurther vision loss. Early treatment can stop additional eyesight loss.Glaucoma can only be identified by a comprehensive Examination ofdilated eyes. For the detection of glaucoma, An architecture for in thispaper image differentiation, CNN provides a Hierarchical picturestructure. CLAHE, grey scaling, and resizing are some of thepreprocessing methods used for images. Additionally, Canny edgedetection is used for additional segmentation. The CNN categorizesThis suggested approach shows the systems reliability and promiseby achieving high classification accuracy along with othercharacteristics.
Copyright
Copyright © 2025 Uvan S. This is an open access article distributed under the Creative Commons Attribution License.