Quantitative retinal imaging is essential for advanced study and clinical management of eye diseases. However, spatial resolution of retinal imaging has been limited due to available numerical aperture and optical aberration of the ocular optics. Structured illumination microscopy has been established to break the diffraction-limit resolution in conventional light microscopy. However, practical implementation of structured illumination microscopy for in vivo ophthalmoscopy of the retina is challenging due to inevitable eye movements that can produce phase artifacts. Recently, we have demonstrated the feasibility of using virtually structured detection as one alternative to structured illumination microscopy for super-resolution imaging. By providing the flexibility of digital compensation of eye movements, the virtually structured detection provides a feasible, phase-artifact-free strategy to achieve super-resolution ophthalmoscopy. In this article, we summarize the technical rationale of virtually structured detection, and its implementations for super-resolution imaging of freshly isolated retinas, intact animals, and awake human subjects.

定量视网膜成像对于眼部疾病的高级研究和临床管理至关重要。然而，由于可用的数值孔径和眼光学器件的光学像差，视网膜成像的空间分辨率受到限制。结构照明显微镜的建立打破了传统光学显微镜的衍射极限分辨率。然而，由于不可避免的眼球运动会产生相位伪影，用于视网膜活体检眼镜检查的结构照明显微镜的实际实施具有挑战性。最近，我们证明了使用虚拟结构化检测作为超分辨率成像结构照明显微镜的一种替代方案的可行性。通过提供眼球运动数字补偿的灵活性，虚拟结构化检测提供了一种可行的、无相位伪影的策略来实现超分辨率检眼镜。在本文中，我们总结了虚拟结构化检测的技术原理，及其对新鲜分离的视网膜、完整动物和清醒人类受试者的超分辨率成像的实现。