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AI-Based Virtual Twin System for Ophthalmology
Professor Shan Suthaharan receives a grant from the University of Pittsburgh for his project “AI-Based Virtual Twin System for Ophthalmology.” This project is supported by funds from the Shear Family Foundation. The main goal of this project is to develop a virtual twin (or a digital twin) of a living human eye by studying a large set (big data) of multimodal retinal image data. In other words, the scope of this virtual twin project is to develop a cohesive set of artificial intelligent (AI) based systems that learn salient characteristics from decades of patient data to allow automated diagnosis and prognosis of an ophthalmological condition. To accomplish this project, Professor Suthaharan will study the optical coherence tomography (OCT), blue autofluorescence (BAF), infrared (IR), and fundus image data, and understand the computational characteristics (features) of retina and the inherent alterations (signatures) that the retinal diseases may generate. These computational structures and disease signatures are generally latent in these modalities; hence, without performing multimodal image registration, it is impossible to detect and extract features from these modalities for developing a virtual twin system of a living human eye.
Therefore, Professor Suthaharan will study this problem using AI techniques and big data systems in collaboration with the ophthalmologists and vision scientists at the University of Pittsburgh School of Medicine and develop an AI-based big data alignment technique for the proposed virtual twin system of a living human eye.
Congratulations to Professor Suthaharan for his AI-based cutting-edge research…!!!