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CLC number: O436

On-line Access: 2024-08-27

Received: 2023-10-17

Revision Accepted: 2024-05-08

Crosschecked: 2017-09-25

Cited: 1

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Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Zhi-ping Zeng

http://orcid.org/0000-0002-4099-6784

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Frontiers of Information Technology & Electronic Engineering  2017 Vol.18 No.9 P.1222-1235

http://doi.org/10.1631/FITEE.1601628


Computational methods in super-resolution microscopy


Author(s):  Zhi-ping Zeng, Hao Xie, Long Chen, Karl Zhanghao, Kun Zhao, Xu-san Yang, Peng Xi

Affiliation(s):  College of Physics and Information Engineering, Fuzhou University, Fuzhou 350116, China; more

Corresponding email(s):   zhipingzeng@fzu.edu.cn, xipeng@pku.edu.cn

Key Words:  Super-resolution microscopy, Deconvolution, Computational methods


Zhi-ping Zeng, Hao Xie, Long Chen, Karl Zhanghao, Kun Zhao, Xu-san Yang, Peng Xi. Computational methods in super-resolution microscopy[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(9): 1222-1235.

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journal="Frontiers of Information Technology & Electronic Engineering",
volume="18",
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pages="1222-1235",
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publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1601628"
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%A Zhi-ping Zeng
%A Hao Xie
%A Long Chen
%A Karl Zhanghao
%A Kun Zhao
%A Xu-san Yang
%A Peng Xi
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%V 18
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%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1601628

TY - JOUR
T1 - Computational methods in super-resolution microscopy
A1 - Zhi-ping Zeng
A1 - Hao Xie
A1 - Long Chen
A1 - Karl Zhanghao
A1 - Kun Zhao
A1 - Xu-san Yang
A1 - Peng Xi
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 18
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SP - 1222
EP - 1235
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Y1 - 2017
PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.1601628


Abstract: 
The broad applicability of super-resolution microscopy has been widely demonstrated in various areas and disciplines. The optimization and improvement of algorithms used in super-resolution microscopy are of great importance for achieving optimal quality of super-resolution imaging. In this review, we comprehensively discuss the computational methods in different types of super-resolution microscopy, including deconvolution microscopy, polarization-based super-resolution microscopy, structured illumination microscopy, image scanning microscopy, super-resolution optical fluctuation imaging microscopy, single-molecule localization microscopy, Bayesian super-resolution microscopy, stimulated emission depletion microscopy, and translation microscopy. The development of novel computational methods would greatly benefit super-resolution microscopy and lead to better resolution, improved accuracy, and faster image processing.

超分辨显微成像技术中的计算方法

概要:超分辨显微成像技术已广泛应用于多个领域。其中,计算方法的优化和提升,对超分辨显微系统成像质量优化至关重要。本文综述了目前主流超分辨显微技术采用的计算方法,包括反卷积显微技术、基于偏振的超分辨显微技术、结构光照明显微技术、图像扫描显微技术、超分辨光学涨落显微成像技术、单分子定位显微技术、贝叶斯分析超分辨显微技术、受激辐射损耗显微技术和移位显微技术。新计算方法的发展将有助于提升超分辨显微的成像效果,使其具备更好的分辨率、更高的精度和更快的图像处理速度。

关键词:超分辨显微;反卷积;计算方法

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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