1. An Intelligent Optical Coherence Tomography-based System for Pathological Retinal Cases Identification and Urgent Referrals

    An Intelligent Optical Coherence Tomography-based System for Pathological Retinal Cases Identification and Urgent Referrals

    Purpose : This study aimed to develop an automated system with artificial intelligence algorithms to comprehensively identify pathologic retinal cases and make urgent referrals. Methods : To build and test the intelligent system, this study obtained 28,664 optical coherence tomography (OCT) images from 2254 patients in the Eye and ENT Hospital of Fudan University (EENT Hospital) and Shanghai Tenth People's Hospital (TENTH Hospital). We applied a deep learning model with an adapted feature pyramid network to detect 15 categories of retinal pathologies from OCT images as common signs of various retinal diseases. Subsequently, the pathologies detected in the OCT images ...

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