The pyramid wavefront sensor (P-WFS) has replaced the Shack-Hartmann (SH-) WFS as the sensor of choice for high-performance adaptive optics (AO) systems in astronomy. Many advantages of the P-WFS, such as its adjustable pupil sampling and superior sensitivity, are potentially of great benefit for AO-supported imaging in ophthalmology as well. However, so far no high quality ophthalmic AO imaging was achieved using this novel sensor. Usually, a P-WFS requires modulation and high precision optics that lead to high complexity and costs of the sensor. These factors limit the competitiveness of the P-WFS with respect to other WFS devices for AO correction in visual science. Here, we present a cost-effective realization of AO correction with a non-modulated P-WFS based on standard components and apply this technique to human retinal in vivo imaging using optical coherence tomography (OCT). P-WFS based high quality AO imaging was successfully performed in 5 healthy subjects and smallest retinal cells such as central foveal cone photoreceptors are visualized. The robustness and versatility of the sensor is demonstrated in the model eye under various conditions and in vivo by high-resolution imaging of other structures in the retina using standard and extended fields of view. As a quality benchmark, the performance of conventional SH-WFS based AO was used and successfully met. This work may trigger a paradigm shift with respect to the wavefront sensor of choice for AO in ophthalmic imaging.

中文翻译：

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使用金字塔波前传感器的视网膜自适应光学成像

金字塔波前传感器 (P-WFS) 已取代 Shack-Hartmann (SH-) WFS，成为天文学中高性能自适应光学 (AO) 系统的首选传感器。P-WFS 的许多优点，例如其可调节的瞳孔采样和卓越的灵敏度，对于眼科中 AO 支持的成像也有很大的好处。然而，到目前为止，使用这种新型传感器还没有实现高质量的眼科 AO 成像。通常，P-WFS 需要调制和高精度光学器件，这会导致传感器的高复杂性和成本。这些因素限制了 P-WFS 相对于其他用于视觉科学 AO 校正的 WFS 设备的竞争力。在这里，我们提出了一种基于标准组件的非调制 P-WFS 的 AO 校正的成本效益实现，并将该技术应用于人类视网膜使用光学相干断层扫描 (OCT)进行体内成像。基于 P-WFS 的高质量 AO 成像在 5 名健康受试者中成功进行，并且最小的视网膜细胞如中央凹锥光感受器被可视化。通过使用标准和扩展视野对视网膜中的其他结构进行高分辨率成像，在各种条件下和体内模型眼中证明了传感器的稳健性和多功能性。作为质量基准，使用并成功满足了基于传统 SH-WFS 的 AO 的性能。这项工作可能会引发眼科成像中 AO 选择的波前传感器的范式转变。