[论文解读] Adaptive optical focusing through perturbed scattering media with dynamic mutation algorithm

Huanhao Li, Chi Man Woo+7 more|arXiv (Cornell University)|Oct 17, 2020

Random lasers and scattering media参考文献 26被引用 8

一句话总结

本文提出一种用于通过散射介质实现自适应光学聚焦的动态突变算法，利用理论上证明的二元振幅调制平方规则，实时量化波前误差。该方法通过根据实时聚焦性能指标动态调整空间光调制器，实现了在突发扰动后快速恢复聚焦光束，这是传统迭代算法此前无法实现的。

ABSTRACT

Optical focusing through/inside scattering media, like multimode fiber and biological tissues, has significant impact in biomedicine yet considered challenging due to strong scattering nature of light. Previously, promising progress has been made, benefiting from the iterative optical wavefront shaping, with which deep-tissue high-resolution optical focusing becomes possible. Most of iterative algorithms can overcome noise perturbations but fail to effectively adapt beyond the noise, e.g. sudden strong perturbations. Re-optimizations are usually needed for significant decorrelated medium since these algorithms heavily rely on the optimization in the previous iterations. Such ineffectiveness is probably due to the absence of a metric that can gauge the deviation of the instant wavefront from the optimum compensation based on the concurrently measured optical focusing. In this study, a square rule of binary-amplitude modulation, directly relating the measured focusing performance with the error in the optimized wavefront, is theoretically proved and experimentally validated. With this simple rule, it is feasible to quantify how many pixels on the spatial light modulator incorrectly modulate the wavefront for the instant status of the medium or the whole system. As an example of application, we propose a novel algorithm, dynamic mutation algorithm, with high adaptability against perturbations by probing how far the optimization has gone toward the theoretically optimum. The diminished focus of scattered light can be effectively recovered when perturbations to the medium cause significant drop of the focusing performance, which no existing algorithms can achieve due to their inherent strong dependence on previous optimizations. With further improvement, this study may boost or inspire many applications, like high-resolution imaging and stimulation, in instable scattering environments.

研究动机与目标

• 克服现有迭代波前整形算法在散射介质中遭遇突发强扰动时无法适应的局限性。
• 解决在优化过程中缺乏实时衡量波前补偿偏离最优状态程度的指标的问题。
• 实现在生物组织或多模光纤等不稳定散射环境中的鲁棒光学聚焦。
• 开发一种减少对先前优化历史依赖的方法，实现在去相关后快速重新优化。
• 验证理论上的平方规则，该规则将二元振幅调制与波前误差关联，用于实时性能监控。

提出的方法

• 理论上推导出二元振幅调制与波前误差之间的平方规则，实现对空间光调制器上错误相位像素的直接量化。
• 利用实时光学聚焦性能测量，计算当前与最优波前补偿之间的偏差。
• 设计动态突变算法，基于误差指标探测优化距离理论最优值的远近。
• 实现反馈回路，通过误差指标识别出的高误差像素选择性地突变，以调整波前校正。
• 在介质特性突然变化的动态散射环境中应用该算法，例如组织运动或光纤扰动期间。
• 通过空间光调制器和波前传感的实验验证，实时测量聚焦强度并校正扰动。

实验结果

研究问题

• RQ1 能否推导出一种实时指标，用于量化散射介质中波前误差相对于最优补偿的程度？
• RQ2 如何使波前整形算法对导致介质去相关的突发强扰动具备鲁棒性？
• RQ3 动态突变算法在介质扰动导致聚焦性能显著下降后，能在多大程度上恢复光学聚焦？
• RQ4 二元振幅调制的平方规则能否在实验中被验证为波前误差的可靠指示器？
• RQ5 减少对先前优化历史的依赖，是否能提升在不稳定散射环境中重新优化的速度与鲁棒性？

主要发现

• 二元振幅调制的平方规则在理论上得到证明，并通过实验验证，实现了对空间光调制器上错误调制像素的波前误差直接量化。
• 动态突变算法在导致聚焦性能显著下降的严重扰动后，成功恢复了聚焦光束，这是现有迭代算法所不具备的能力。
• 该方法通过基于实时性能反馈动态调整校正，表现出高度适应性，减少了对先前优化状态的依赖。
• 实验结果证实，即使介质经历强烈且突发的变化，该算法仍能识别并纠正波前误差。
• 该方法实现了在不稳定散射环境（如生物组织或多模光纤）中的快速重新优化，而传统方法在去相关后失效。
• 本研究通过克服传统波前整形技术的局限性，为动态生物系统中的高分辨率成像与刺激奠定了基础。