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A Deep Learning Method for Automatic Identification of Drusen and Macular Hole from Optical Coherence Tomography
Teresa Pace, Nicolò Degan, Rosa Giglio Md, Daniele Tognetto Md, Agostino Accardo
565 - 566
10.3233/SHTI220525
Research Article
Studies in Health Technology and Informatics
Volume 294: Challenges of Trustable AI and Added-Value on Health
Abstract

Deep Learning methods have become dominant in various fields of medical imaging, including ophthalmology. In this preliminary study, we investigated a method based on Convolutional Neural Network for the identification of drusen and macular hole from Optical Coherence Tomography scans with the aim to assist ophthalmologists in diagnosing and assessing retinal diseases.

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