MUMBAI, India, June 30 -- Intellectual Property India has published a patent application (202641074833 A) filed by Kosuri Srinivasa Rao; Neelapala Anil Kumar; Gnane Swarnadh Satapathi; and Ramchandra V. Shet on June 17, 2026, for Automated Ophthalmic Image Analysis System For Dry Eye Disease Prediction Using Hybrid Deep Learning Framework.
Inventors include Kosuri Srinivasa Rao; Neelapala Anil Kumar; Gnane Swarnadh Satapathi; and Ramchandra V. Shet.
The application for the patent was published on June 26, 2026, under issue no. 26/2026.
Abstract: The present invention discloses an automated ophthalmic image analysis system and method for Dry Eye Disease prediction using a hybrid deep learning framework. The system acquires ophthalmic images including tear film, corneal, meibography, and ocular surface images and performs preprocessing operations such as normalization, enhancement, and segmentation. A hybrid deep learning architecture comprising Convolutional Neural Networks, Vision Transformers, attention mechanisms, and feature fusion modules extracts discriminative features for disease prediction. The extracted features are analyzed by a classification engine to identify Dry Eye Disease severity levels. An Explainable Artificial Intelligence module generates visual explanations including heatmaps and attention maps for clinical interpretability. The invention improves diagnostic accuracy, reduces observer variability, enables real-time screening, and provides intelligent decision support for ophthalmologists in clinical and telemedicine environments.
Disclaimer: Curated by HT Syndication.
