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Proceedings Paper

Large scale superres 3D imaging: light-sheet single-molecule localization microscopy (Conference Presentation)
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Paper Abstract

Optical imaging techniques provide much important information in understanding life science especially cellular structure and morphology because “seeing is believing”. However, the resolution of optical imaging is limited by the diffraction limit, which is discovered by Ernst Abbe, i.e. λ/2(NA) (NA is the numerical aperture of the objective lens). Fluorescence super-resolution microscopic techniques such as Stimulated emission depletion microscopy (STED), Photoactivated localization microscopy (PALM), and Stochastic optical reconstruction microscopy (STORM) are invented to have the capability of seeing biological entities down to molecular level that are smaller than the diffraction limit (around 200-nm in lateral resolution). These techniques do not physically violate the Abbe limit of resolution but exploit the photoluminescence properties and labelling specificity of fluorescence molecules to achieve super-resolution imaging. However, these super-resolution techniques limit most of their applications to the 2D imaging of fixed or dead samples due to the high laser power needed or slow speed for the localization process. Extended from 2D imaging, light sheet microscopy has been proven to have a lot of applications on 3D imaging at much better spatiotemporal resolutions due to its intrinsic optical sectioning and high imaging speed. Herein, we combine the advantage of localization microscopy and light-sheet microscopy to have super-resolved cellular imaging in 3D across large field of view. With high-density labeled spontaneous blinking fluorophore and wide-field detection of light-sheet microscopy, these allow us to construct 3D super-resolution multi-cellular imaging at high speed (~minutes) by light-sheet single-molecule localization microscopy.

Paper Details

Date Published: 24 April 2017
PDF: 1 pages
Proc. SPIE 10076, High-Speed Biomedical Imaging and Spectroscopy: Toward Big Data Instrumentation and Management II, 1007614 (24 April 2017); doi: 10.1117/12.2257019
Show Author Affiliations
Chieh Han Lu, Research Ctr. for Applied Sciences - Academia Sinica (Taiwan)
Peilin Chen, Research Ctr. for Applied Sciences - Academia Sinica (Taiwan)
Bi-Chang Chen, Research Ctr. for Applied Sciences - Academia Sinica (Taiwan)


Published in SPIE Proceedings Vol. 10076:
High-Speed Biomedical Imaging and Spectroscopy: Toward Big Data Instrumentation and Management II
Kevin K. Tsia; Keisuke Goda, Editor(s)

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