Summary The goal of the proposed project is to develop EyeStar-BIO, a suite of software tools designed to enhance digital binocular indirect ophthalmoscopy examinations (BIO), one of the most common forms of examination of the retina. Using BIO, an ophthalmologist can determine the presence of multiple retinal diseases such as diabetic retinopathy, macular degeneration, and retinopathy of prematurity, among others. The traditional BIO exam does not produce any visual documentation. EyeStar-BIO will feature innovative features that are not currently offered as part of digital BIO exams: (1) automatic image quality assessment, (2) automatic stitching to create a wide-field view of the retina, (3) longitudinal analysis, and (4) AI-based disease detection. This project has an $800M market potential as BIO examinations remain one of the most common procedures for ophthalmologists. The goals of this Phase I project will be accomplished via three specific aims. Aim 1: implement software for automatic image quality assessment of digital BIO video frames. Aim 2: develop image stitching methods to generate a wide field view of the retina using the best quality frames in the video. Aim 3: generate images to track differences in time due to disease progression or regression. The EyeStar-BIO software will be licensed to manufacturers of digital BIO headsets. Future developments will include real time implementations of EyeStar-BIO and the ability to diagnose retinal disease using artificial intelligence.