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		<Title>GENERATIVEADVERSARIALNETWORKSFORRETINAL IMAGE ENHANCEMENT WITH PATHOLOGICAL INFORMATION</Title>
		<Author>ROUTHU.AKHILESWARARAO,SHAIK. RIYAZ PASHA,SHAIK.MD.RABBANI,SRIGADHI.BHANUTEJA</Author>
		<Volume>02</Volume>
		<Issue>03</Issue>
		<Abstract>Agerelated macular degeneration AMD is a disease of the central retina which is one of the main reasons for vision loss of elderly people To monitor the level of AMD the doctors mainly use the retinal fundus images However the quality of retinal images can be affected during the imaging process It leads to low contrast and blurry images Those bad quality images cannot be used for analyzing and diagnosis For that reason there are many studies about image enhancement in order to improve the quality of retinal photography However previous methods could not guarantee to keep the disease information after the enhancement process Therefore we introduce a generative adversarial model for AMD retinal image enhancement with additional factors to preserve the disease information By exploiting drusen segmentation masks our proposed model can enhance retinal photography quality and keep the pathological information</Abstract>
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<copyright-statement>Copyright (c) Journal of Science Engineering Technology and Management Science. All rights reserved</copyright-statement>
<copyright-year>2026</copyright-year>
</permissions>
		</www.jsetms.com>
		