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具有准周期图案的结构光照成像

Structured illumination imaging with quasi-periodic patterns.

作者信息

Xu Dongli, Ding Jun, Peng Leilei

机构信息

College of Optical Sciences, The University of Arizona, Tucson, Arizona, USA.

Department of Neurosurgery, Stanford University School of Medicine, Palo Alto, California, USA.

出版信息

J Biophotonics. 2020 Jun;13(6):e201960209. doi: 10.1002/jbio.201960209. Epub 2020 Mar 18.

Abstract

Structured illumination microscopy (SIM) is a well-established method for optical sectioning and super-resolution. The core of structured illumination is using a periodic pattern to excite image signals. This work reports a method for estimating minor pattern distortions from the raw image data and correcting these distortions during SIM image processing. The method was tested with both simulated and experimental image data from two-photon Bessel light-sheet SIM. The results proves the method is effective in challenging situations, where strong scattering background exists, signal-to-noise ratio (SNR) is low and the sample structure is sparse. Experimental results demonstrate restoring synaptic structures in deep brain tissue, despite the presence of strong light scattering and tissue-induced SIM pattern distortion.

摘要

结构光照明显微镜(SIM)是一种成熟的光学切片和超分辨率方法。结构照明的核心是使用周期性图案来激发图像信号。本文报道了一种从原始图像数据中估计微小图案失真并在SIM图像处理过程中校正这些失真的方法。该方法通过双光子贝塞尔光片SIM的模拟和实验图像数据进行了测试。结果证明该方法在存在强散射背景、信噪比(SNR)低且样品结构稀疏的具有挑战性的情况下是有效的。实验结果表明,尽管存在强光散射和组织引起的SIM图案失真,但仍能恢复深部脑组织中的突触结构。

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Structured illumination imaging with quasi-periodic patterns.具有准周期图案的结构光照成像
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