New AI Method Revolutionizes Eye Hypertension Detection in Fundus Images

A recent study has introduced a new method for detecting eye-hypertensive diseases using advanced imaging techniques. Researchers Y. Kumar, N. Modi, and A. Koul developed an approach combining deep transfer learning with contour-based morphological analysis to identify signs of eye hypertension in fundus images. The findings aim to improve diagnostic accuracy and provide a more efficient tool for early detection of these conditions. The study highlights the integration of deep transfer learning, which leverages pre-trained neural networks, with detailed contour-based analysis to examine structural changes in the eye captured through fundus imaging. This combination allows for precise identification of abnormalities associated with eye hypertension, a condition that can lead to severe complications if left untreated. The researchers suggest that this technique could enhance current diagnostic practices by offering a non-invasive and reliable alternative for medical professionals analyzing retinal images. Newsflash | Powered by GeneOnline AI Source: GO-AI-ne1 For any suggestion and feedback, please contact us. Date: January 19, 2026