MUMBAI, India, Oct. 5 -- Intellectual Property India has published a patent application (202641115344 A) filed by Sri Eshwar College Of Engineering on September 24, 2026, for Iris: Ai Powered Portable Eye Screening And Multi-Disease Detection System.
Inventors include Dr. G. Sathish Kumar; Shakeer. F; Naveen Kumar. G; and Shankaritha. R.
The application for the patent was published on October 02, 2026, under issue no. 40/2026.
Abstract: The invention relates to an integrated Artificial Intelligence (AI)-enabled retinal imaging and screening system. It aims to help detect and assess the risk of multiple retinal diseases, such as Glaucoma, Diabetic Retinopathy (DR), and Age-Related Macular Degeneration (AMD). The system includes a portable retinal imaging device with a high-resolution camera module, ophthalmic condensing lens, controlled lighting module, Raspberry Pi-based processing unit, wireless communication interface, cloud-enabled database, and a mobile app for automatic retinal analysis and patient management. The imaging device captures high-quality fundus images using an optimized optical setup and sends the images wirelessly to the mobile app. The app uses a trained deep learning AI model to preprocess the retinal images. It identifies specific disease features, including optic disc abnormalities, variations in the cup-to-disc ratio, retinal hemorrhages, microaneurysms, exudates, drusen, and macular abnormalities. The app then classifies diseases and assesses risk probabilities. The system produces detailed diagnostic reports that include disease classification, confidence scores, severity levels, annotated retinal images, screening recommendations, and follow-up suggestions. The invention also offers multilingual user support, secure patient registration, digital medical record management, automated report generation, cloud synchronization, and access for healthcare professionals to conduct clinical reviews. The hardware design includes a custom 3D-printed enclosure that ensures accurate optical alignment between the imaging sensor, condensing lens, lighting source, and the patient's eye. This design improves the consistency of image acquisition while significantly cutting manufacturing costs. Unlike traditional retinal imaging systems that need expensive ophthalmic equipment and specialist operators, this invention provides an affordable, portable, AI-assisted screening platform for initial disease identification and referral support. It does not replace clinical diagnoses made by ophthalmologists but acts as an intelligent decision-support system. It offers probability-based screening for diseases to help healthcare professionals with early diagnosis and treatment planning. This invention is particularly useful in primary healthcare centers, rural hospitals, teleophthalmology services, community screening camps, mobile healthcare units, and areas with limited access to specialized ophthalmic diagnostic equipment. The combination of integrated hardware and software, automated AI analysis, portable design, and low-cost implementation creates an effective, scalable, and accessible solution for screening retinal diseases. This approach can improve early detection rates, reduce preventable vision loss, and enhance access to healthcare.
Disclaimer: Curated by HT Syndication.
