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基于增强图像重组变换算法的用于活细胞成像的多色结构照明显微镜技术。

Multi-color structured illumination microscopy for live cell imaging based on the enhanced image recombination transform algorithm.

作者信息

Zhao Tianyu, Hao Huiwen, Wang Zhaojun, Liang Yansheng, Feng Kun, He Minru, Yun Xue, Bianco Piero R, Sun Yujie, Yao Baoli, Lei Ming

机构信息

MOE Key Laboratory for Non-equilibrium Synthesis and Modulation of Condensed Matter, School of Physics, Xi'an Jiaotong University, Xi'an 710049, China.

State Key Laboratory of Transient Optics and Photonics, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, Shaanxi 710119, China.

出版信息

Biomed Opt Express. 2021 May 17;12(6):3474-3484. doi: 10.1364/BOE.423171. eCollection 2021 Jun 1.

Abstract

Structured illumination microscopy (SIM) has attracted considerable interest in super-resolution, live-cell imaging because of its low light dose and high imaging speed. Obtaining a high-quality reconstruction image in SIM depends on the precise determination of the parameters of the fringe illumination pattern. The image recombination transform (IRT) algorithm is superior to other algorithms in obtaining the precise initial phase without any approximation, which is promising to provide a considerable solution to address the difficulty of initial phase estimation at low-modulation-depth conditions. However, the IRT algorithm only considers a phase shift of π∕2, which limits its applications in general scenarios. In this letter, we present a general form of IRT algorithm suitable for arbitrary phase shifts, providing a powerful tool for parameter estimation in low signal-to-noise cases. To demonstrate the effectiveness of the enhanced IRT algorithm, we constructed a multicolor, structured illumination microscope and studied at super-resolution, the cargo traffic in HRPE cells, and monitored the movement of mitochondrial structures and microtubules in COS-7 cells. The custom SIM system using the enhanced IRT algorithm allows multicolor capability and a low excitation intensity fluorescence imaging less than 1 W/cm. High-quality super-resolution images are obtained, which demonstrates the utility of this approach in imaging in the life sciences.

摘要

结构光照明显微镜(SIM)因其低光剂量和高成像速度,在超分辨率活细胞成像方面引起了广泛关注。在SIM中获得高质量的重建图像取决于条纹照明图案参数的精确确定。图像重组变换(IRT)算法在无任何近似情况下获得精确初始相位方面优于其他算法,有望为解决低调制深度条件下的初始相位估计难题提供一个重要解决方案。然而,IRT算法仅考虑了π∕2的相移,这限制了其在一般场景中的应用。在本文中,我们提出了一种适用于任意相移的IRT算法通用形式,为低信噪比情况下的参数估计提供了一个强大工具。为了证明增强型IRT算法的有效性,我们构建了一台多色结构光照明显微镜,并在超分辨率下研究了HRPE细胞中的货物运输,监测了COS-7细胞中线粒体结构和微管的运动。使用增强型IRT算法的定制SIM系统具有多色功能,激发强度低于1W/cm²的低强度荧光成像。获得了高质量的超分辨率图像,这证明了该方法在生命科学成像中的实用性。

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