...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Optics Letters >Gradient-assisted focusing light through scattering media
【24h】

Gradient-assisted focusing light through scattering media

机译：通过散射介质梯度辅助聚焦光

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Focusing light through a scattering medium is a long-standing challenge in biomedical optics, to which wavefront shaping is a powerful solution. The state-of-the-art feedback-based approach is the widely used genetic algorithm method. However, it can only achieve relatively low enhancement of the focus, and the genetic algorithm is known to be time-consuming. To tackle those issues, we propose a gradient-assisted strategy for wavefront shaping. The proposed method conducts optimization in the function distribution space. Specifically, when optimizing the parameters along each iteration, the consequent function distribution changes within a distance as measured by the Kullback-Leibler divergence. Taking advantage of the gradient information, the proposed method is over 60x faster to obtain the same peak-to-background ratio (PBR) level. Compared with the genetic algorithm that is able to optimize a number of 64 x 64 phase segments, the proposed gradient strategy is able to optimize 256 x 256 phase segments, and gives 20x higher focus enhancement as quantified by the PBR. (C) 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
机译：在生物医学光学中，通过散射介质聚焦光是一个长期存在的挑战，波前整形是一个强有力的解决方案。最先进的基于反馈的方法是广泛使用的遗传算法方法。然而，它只能实现相对较低的焦点增强，而且众所周知，遗传算法非常耗时。为了解决这些问题，我们提出了一种梯度辅助波前整形策略。该方法在函数分布空间中进行优化。具体地说，当沿着每次迭代优化参数时，随后的函数分布会在Kullback-Leibler散度测量的距离内发生变化。利用梯度信息，该方法获得相同峰值背景比（PBR）水平的速度超过60倍。与能够优化多个64 x 64相位段的遗传算法相比，所提出的梯度策略能够优化256 x 256相位段，并使PBR量化的聚焦增强提高20倍。（c）OSA开放获取出版协议条款下的美国2021光学学会

著录项

  • 来源
    《Optics Letters》 |2021年第7期|共4页
  • 作者

    Zhao Yanyu; He Qiaozhi; Li Shuna; Yang Jiamiao;

  • 作者单位

    Beihang Univ Beijing Adv Innovat Ctr Biomed Engn Key Lab Biomech &

    Mechanobiol Minist Educ Sch Biol Sci &

    Med Engn Beijing 100191 Peoples R China;

    Shanghai Jiao Tong Univ Sch Elect Informat &

    Elect Engn Dept Instrument Sci &

    Engn Shanghai 200240 Peoples R China;

    North Univ China Sch Informat &

    Commun Engn Taiyuan 030051 Peoples R China;

    Shanghai Jiao Tong Univ Sch Elect Informat &

    Elect Engn Dept Instrument Sci &

    Engn Shanghai 200240 Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 计量学;光学;
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号