• B.Purna Chandra Sekhar
• V.Geetha Sudheshna
• T.Sree Vyshnavi
• Y.Rishi
• Mr.P.Yugandhar Reddy

The size, dimension, shape of the blood vessels in the retina are significant anatomical traits that help determine the prevalence of hypertension, diabetes, and heart disease. In this work, segmenting of the retina arteries based on the spectral fundus pictures are processed using deep learning approaches. The retina Arteries can be characterised to diagnose a variety of eye illnesses. With the use of appropriate image processing approaches and data analytics procedures, classification can be derived. To detect the variety of cardiovascular and ophthalmologic disorders, including diabetes, hypertension, and arteriosclerosis. Utilising U-Net Architecture, vessels are segmented. Our technique is assessed on the DRIVE Dataset.

Retina, Convolutional, U-Net, vessel, Opthalmology.

"Retina Vessel Segmentation Using U-Net Architecture", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 5, page no.o557-o562, May-2024, Available :http://www.jetir.org/papers/JETIR2405F61.pdf

"Retina Vessel Segmentation Using U-Net Architecture", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 5, page no. ppo557-o562, May-2024, Available at : http://www.jetir.org/papers/JETIR2405F61.pdf