论文标题
Debye-Wolf积分的可区分优化，用于在两光子显微镜下进行光塑形和自适应光学元件
Differentiable optimization of the Debye-Wolf integral for light shaping and adaptive optics in two-photon microscopy
论文作者
论文摘要
通过具有高数值孔径的显微镜物镜控制光是在光遗传学，自适应光学或激光处理等应用中的共同要求。光传播（包括极化效应）可以在这些条件下使用Debye-Wolf衍射积分来描述。在这里，我们利用可区分的优化和机器学习，以有效地优化了此类应用程序的Debye-Wolf积分。对于光塑形，我们表明这种优化方法适用于两光子显微镜中的工程任意三维点扩散功能。对于基于模型的自适应光学器件（DAO），开发的方法可以找到具有固有图像特征的像差校正，例如用遗传编码的钙指标标记的神经元，而无需指导星。使用计算模型，我们进一步讨论了可以用这种方法校正的空间频率和差距的范围。
Control of light through a microscope objective with a high numerical aperture is a common requirement in applications such as optogenetics, adaptive optics, or laser processing. Light propagation, including polarization effects, can be described under these conditions using the Debye-Wolf diffraction integral. Here, we take advantage of differentiable optimization and machine learning for efficiently optimizing the Debye-Wolf integral for such applications. For light shaping we show that this optimization approach is suitable for engineering arbitrary three-dimensional point spread functions in a two-photon microscope. For differentiable model-based adaptive optics (DAO), the developed method can find aberration corrections with intrinsic image features, for example neurons labeled with genetically encoded calcium indicators, without requiring guide stars. Using computational modeling we further discuss the range of spatial frequencies and magnitudes of aberrations which can be corrected with this approach.
