作者: Thuss Sanguansak , Katharine Morley , Michael Morley , Suwat Kusakul , Ramon Lee
关键词: Visual acuity 、 Medicine 、 Nuclear medicine 、 Computer vision 、 Artificial intelligence 、 Cataract surgery 、 Clinical competence 、 Post operative 、 Image quality 、 Anterior Eye Segment 、 Slit lamp 、 After cataract
摘要: Introduction The goal of this study is to compare image quality and clinical confidence for managing post-operative cataract patients based on anterior segment smartphone images obtained in real-world settings using four types adapters: (a) macro lens (ML), (b) ML with augmented light-emitting diode (LED) illumination (ML-LED), (c) no adapter (NA) (d) slit lamp (SL) adapter. Methods Anterior were from 190 eyes after surgery an eight-megapixel iPhone 6 camera ML, ML-LED, NA, SL. Smartphone subjectively rated by ophthalmologists as acceptable or not for: evaluating the structures reader clinically images. Results SL had highest scores 100%, 93.7%, 86.3% judged acceptable, respectively. SL, ML-LED also 98%, 93.2% having levels, was lowest both (61.1% acceptable) (37.4% acceptable). Discussion This represents first effort different adapters' ability eye a setting. Our shows that adapters visualizing physician readers 86-100% cases. When coupled visual acuity, intro-ocular pressure history, these can result 93-100%