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超分辨率结构光照明显微镜重建算法综述

Superresolution structured illumination microscopy reconstruction algorithms: a review.

作者信息

Chen Xin, Zhong Suyi, Hou Yiwei, Cao Ruijie, Wang Wenyi, Li Dong, Dai Qionghai, Kim Donghyun, Xi Peng

机构信息

Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, 100871, China.

National Biomedical Imaging Center, Peking University, Beijing, 100871, China.

出版信息

Light Sci Appl. 2023 Jul 12;12(1):172. doi: 10.1038/s41377-023-01204-4.

Abstract

Structured illumination microscopy (SIM) has become the standard for next-generation wide-field microscopy, offering ultrahigh imaging speed, superresolution, a large field-of-view, and long-term imaging. Over the past decade, SIM hardware and software have flourished, leading to successful applications in various biological questions. However, unlocking the full potential of SIM system hardware requires the development of advanced reconstruction algorithms. Here, we introduce the basic theory of two SIM algorithms, namely, optical sectioning SIM (OS-SIM) and superresolution SIM (SR-SIM), and summarize their implementation modalities. We then provide a brief overview of existing OS-SIM processing algorithms and review the development of SR-SIM reconstruction algorithms, focusing primarily on 2D-SIM, 3D-SIM, and blind-SIM. To showcase the state-of-the-art development of SIM systems and assist users in selecting a commercial SIM system for a specific application, we compare the features of representative off-the-shelf SIM systems. Finally, we provide perspectives on the potential future developments of SIM.

摘要

结构光照明显微镜(SIM)已成为下一代宽视场显微镜的标准,具有超高成像速度、超分辨率、大视场和长期成像能力。在过去十年中,SIM的硬件和软件蓬勃发展,在各种生物学问题上都有成功应用。然而,要释放SIM系统硬件的全部潜力,需要开发先进的重建算法。在这里,我们介绍两种SIM算法的基本理论,即光学切片SIM(OS-SIM)和超分辨率SIM(SR-SIM),并总结它们的实现方式。然后,我们简要概述现有的OS-SIM处理算法,并回顾SR-SIM重建算法的发展,主要集中在二维SIM、三维SIM和盲SIM上。为了展示SIM系统的最新发展,并帮助用户为特定应用选择商用SIM系统,我们比较了代表性现货SIM系统的特点。最后,我们对SIM未来的潜在发展提供了展望。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/88a5/10336069/57dac2458f48/41377_2023_1204_Fig1_HTML.jpg

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