Optical coherence tomographic angiography (OCTA) is a non-invasive imaging modality that provides three-dimensional, information-rich vascular images. With numerous studies demonstrating unique capabilities in biomarker quantification, diagnosis, and monitoring, OCTA technology has seen rapid adoption in research and clinical settings. The value of OCTA imaging is significantly enhanced by image analysis tools that provide rapid and accurate quantification of vascular features and pathology. Today, the most powerful image analysis methods are based on artificial intelligence (AI). While AI encompasses a large variety of techniques, machine-learning-based, and especially deep-learning-based, image analysis provides accurate measurements in a variety of contexts, including different diseases and regions of the eye. Here, we discuss the principles of both OCTA and AI that make their combination capable of answering new questions. We also review contemporary applications of AI in OCTA, which include accurate detection of pathologies such as choroidal neovascularization, precise quantification of retinal perfusion, and reliable disease diagnosis.

光学相干断层扫描血管造影 (OCTA) 是一种非侵入性成像方式，可提供三维、信息丰富的血管图像。大量研究证明了 OCTA 技术在生物标志物定量、诊断和监测方面的独特能力，已在研究和临床环境中得到快速采用。图像分析工具可以快速、准确地量化血管特征和病理，从而显着增强了 OCTA 成像的价值。如今，最强大的图像分析方法基于人工智能 (AI)。虽然人工智能涵盖了多种基于机器学习，尤其是基于深度学习的技术，但图像分析可以在各种情况下提供准确的测量，包括不同的疾病和眼睛区域。在这里，我们讨论 OCTA 和人工智能的原理，使它们的组合能够回答新问题。我们还回顾了人工智能在 OCTA 中的当代应用，其中包括脉络膜新生血管等病理学的准确检测、视网膜灌注的精确量化以及可靠的疾病诊断。