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20 September 2016 Image recombination transform algorithm for superresolution structured illumination microscopy
Xing Zhou, Ming Lei, Dan Dan, Baoli Yao, Yanlong Yang, Jia Qian, Guangde Chen, Piero R. Bianco
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Journal of Biomedical Optics, Vol. 21, Issue 9, 096009 (September 2016). https://doi.org/10.1117/1.JBO.21.9.096009
Abstract
Structured illumination microscopy (SIM) is an attractive choice for fast superresolution imaging. The generation of structured illumination patterns made by interference of laser beams is broadly employed to obtain high modulation depth of patterns, while the polarizations of the laser beams must be elaborately controlled to guarantee the high contrast of interference intensity, which brings a more complex configuration for the polarization control. The emerging pattern projection strategy is much more compact, but the modulation depth of patterns is deteriorated by the optical transfer function of the optical system, especially in high spatial frequency near the diffraction limit. Therefore, the traditional superresolution reconstruction algorithm for interference-based SIM will suffer from many artifacts in the case of projection-based SIM that possesses a low modulation depth. Here, we propose an alternative reconstruction algorithm based on image recombination transform, which provides an alternative solution to address this problem even in a weak modulation depth. We demonstrated the effectiveness of this algorithm in the multicolor superresolution imaging of bovine pulmonary arterial endothelial cells in our developed projection-based SIM system, which applies a computer controlled digital micromirror device for fast fringe generation and multicolor light-emitting diodes for illumination. The merit of the system incorporated with the proposed algorithm allows for a low excitation intensity fluorescence imaging even less than 1  W/cm2, which is beneficial for the long-term, in vivo superresolved imaging of live cells and tissues.
CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
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Xing Zhou, Ming Lei, Dan Dan, Baoli Yao, Yanlong Yang, Jia Qian, Guangde Chen, and Piero R. Bianco "Image recombination transform algorithm for superresolution structured illumination microscopy," Journal of Biomedical Optics 21(9), 096009 (20 September 2016). https://doi.org/10.1117/1.JBO.21.9.096009
Published: 20 September 2016
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Cited by 40 scholarly publications.
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KEYWORDS
Reconstruction algorithms
Super resolution
Modulation
Phase shift keying
Microscopy
Imaging systems
Luminescence
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