Diener R, Treder M, Eter N
Klinik für Augenheilkunde, Universitätsklinikum Münster, Domagkstr. 15, 48149, Münster, Deutschland.
Ophthalmologe. 2021 Sep;118(9):893-899. doi: 10.1007/s00347-021-01385-6. Epub 2021 Apr 22.
The use of artificial intelligence (AI) interesting for automated image segmentation, analysis and classification, among others and has already been described for various fields of ophthalmology.
This manuscript provides an overview of current approaches and advances in the application of big data and AI in various diseases of the optic nerve head.
A PubMed search was performed. Studies were searched for that answered clinical questions using big data approaches or classical machine learning methods in the analysis of multimodal imaging of the optic nerve head.
Big data can help to answer clinical questions in common diseases such as glaucoma. The AI is applied for the segmentation of multimodal imaging of the optic nerve head as well as for the classification of diseases, such as glaucoma or optic disc edema on this imaging data.
With the help of big data and AI, relationships can be recognized more easily and the diagnostics and course assessment of diseases of the optic nerve head can be facilitated or automated. A prerequisite for clinical application is a CE marking as a medical device in Europe and approval by the Food and Drug Administration in the USA.
人工智能（AI）在自动图像分割、分析和分类等方面的应用颇受关注，并且已经在眼科的各个领域有所描述。
本文综述了大数据和人工智能在视神经乳头各种疾病应用中的当前方法和进展。
进行了PubMed检索。检索了使用大数据方法或经典机器学习方法分析视神经乳头多模态成像以回答临床问题的研究。
大数据有助于回答青光眼等常见疾病的临床问题。人工智能应用于视神经乳头多模态成像的分割以及基于此成像数据的疾病分类，如青光眼或视盘水肿。
借助大数据和人工智能，可以更轻松地识别关系，促进或自动化视神经乳头疾病的诊断和病程评估。临床应用的一个先决条件是在欧洲作为医疗器械获得CE标志，并在美国获得食品药品监督管理局的批准。
