Next-Generation Teleophthalmology: AI-enabled Quality Assessment Aiding Remote Smartphone-based Consultation

February 11, 2024 Β· Declared Dead Β· πŸ› Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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Authors Dhruv Srikanth, Jayang Gurung, N Satya Deepika, Vineet Joshi, Lopamudra Giri, Pravin Vaddavalli, Soumya Jana arXiv ID 2402.07118 Category cs.HC: Human-Computer Interaction Cross-listed cs.AI, cs.LG, eess.IV, eess.SP Citations 1 Venue Annual International Conference of the IEEE Engineering in Medicine and Biology Society Last Checked 4 months ago
Abstract
Blindness and other eye diseases are a global health concern, particularly in low- and middle-income countries like India. In this regard, during the COVID-19 pandemic, teleophthalmology became a lifeline, and the Grabi attachment for smartphone-based eye imaging gained in use. However, quality of user-captured image often remained inadequate, requiring clinician vetting and delays. In this backdrop, we propose an AI-based quality assessment system with instant feedback mimicking clinicians' judgments and tested on patient-captured images. Dividing the complex problem hierarchically, here we tackle a nontrivial part, and demonstrate a proof of the concept.
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