摘要
近年来，深度学习算法已成为计算机科学研究的重要前沿领域，并在图像识别、语音识别及自然语言处理等领域得到广泛应用，但其与医疗领域的融合起步较晚。将深度学习算法用于眼底照相、光学相干断层扫描及视野检查等眼部常规检查中可有效地评估青光眼、白内障、年龄相关性黄斑变性及糖尿病性视网膜病变等常见致盲性眼病的风险。目前，该算法在眼科常见疾病筛查与诊断中的实用性已得到充分证明。本文中笔者从青光眼筛查与诊断的角度就该算法在其中应用的研究进展进行综述。
Abstract
In recent years, deep learning has become an important cutting-edge field of computer science research, which has been widely used in image recognition, speech recognition and natural language processing. But its lateral integration on the medical field has not been yet fully developped. The application of deep learning in ophthalmic examinations including fundus photography, optical coherence tomography and visual field examination can effectively screen and evaluate a variety of common blinding eye diseases including glaucoma, cataract, age-related macular degeneration and diabetic retinopathy. Currently, it has been fully proved its practicability in the screening and diagnosis of common ophthalmic diseases. In this paper, the application of deep learning technology in the screening, diagnosis of glaucoma and the future research direction was reviewed.
基金项目
国家自然科学基金(81970801)
湖南省自然科学基金(2023JJ70014)
湖南省自然科学基金(2019JJ40001)
湖南省重点领域研发计划资助项目(2020SK2133)
爱尔眼科医院集团科研基金(AR2206D5)
万方数据