A universal framework for microscope sensorless adaptive optics: Generalized aberration representations
A universal framework for microscope sensorless adaptive optics: Generalized aberration representations
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DOI：
10.1063/5.0022523
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发表时间：
2020-10-01
期刊：
影响因子：
5.6
通讯作者：
Booth, M. J.
中科院分区：
文献类型：
--
作者：
Hu, Q.;Wang, J.;Booth, M. J.
自适应光学(AO)方法被广泛应用于显微镜中，通过校正位相像差来改善图像质量。存在一系列无波前传感器的光学方法，如模态法、光瞳分割法和像素化的活塞法。其中的每一个都有不同的物理实现，这使得直接比较变得困难。在这里，我们提出了一个框架，适用于所有的无传感器声学方法，并促进了它们之间的系统比较。我们介绍了一个包含许多现有方法的象差表示的通用模型。通过在双光子显微镜上的建模和实验验证，我们比较了具有各种像差表示的无传感器光学光学方案，以校正模拟像差和样品诱导的像差。结果表明，在不同的实验场景中，不同的表示形式可以为校正提供更好的依据，从而为特定应用的无传感器声光方案的选择提供参考。
Adaptive optics (AO) methods are widely used in microscopes to improve image quality through correction of phase aberrations. A range of wavefront-sensorless AO schemes exist, such as modal, pupil segmentation zonal, and pixelated piston-based methods. Each of these has a different physical implementation that makes direct comparisons difficult. Here, we propose a framework that fits in all sensorless AO methods and facilitates systematic comparisons among them. We introduce a general model for the aberration representation that encompasses many existing methods. Through modeling and experimental verification in a two-photon microscope, we compared sensorless AO schemes with a range of aberration representations to correct both simulated and sample induced aberrations. The results show that different representations can provide a better basis for correction in different experimental scenarios, which can inform the choice of sensorless AO schemes for a particular application.