基于深度学习人工智能辅助诊断糖尿病视网膜病变研究现状及展望

Research status and prospect of deep learning algorithm-based artificial intelligence in assisted diagnosis of diabetic retinopathy

基于深度学习的人工智能(AI)技术的快速进展使得眼科疾病的AI影像分析成为可能,近年来相关的基础研究和临床应用研究取得了令人瞩目的进步。利用彩色眼底照片表现的信息,AI可对糖尿病视网膜病变(DR)进行自动分析和辅助诊断。目前相较于其他眼科疾病,AI技术在DR辅助诊断中的应用研究进展更快,技术逐渐成熟。AI辅助诊断速度快、准确率高,可节省医务人员的劳动力资源,在DR辅助筛查和分级应用方面展现出很大的潜力。AI是近年来发展的一种基于深度学习的智能系统,该研究领域涉及多学科知识和技术的深度融合,需要多学科技术资源的配合和共享,目前仍然存在数据标准化、临床验证不足及产品待落地等问题。尽管AI辅助的DR筛查研究机遇与挑战并存,但随着研究的逐渐深入和相关交叉学科研究者的共同努力,AI辅助诊断DR研究在眼科临床的实践有望取得更大的进步。

Based on deep learning algorithm,big stride development has been made about artificial intelligence (AI) technology,both in its basic theory and clinical ophthalmic image analysis.AI can diagnose diabetic retinopathy (DR) automatically by using color fundus photography.Compared with other ophthalmic diseases,DR assisted diagnosis with AI might be far more advanced technic.Benefited from advantage of fast diagnostic speed,high accuracy and accordingly saved human resources,great potential can be expected in AI-assisted DR screening and grading.However,as a recently developed interdisciplinary technology,deep learning-based AI-aided DR screening system still needs multidisciplinary cooperation and resources sharing to get further development,such as overcoming data standardization,real-world verification and productization issues.Although challenges coexist,AI applied in ophthalmology clinical practice can be realized with technical development and widespread concern of society.