Single Molecule Localization Microscopy (SMLM) techniques such as Photo-Activation Localization Microscopy (PALM) and Stochastic Optical Reconstruction Microscopy (STORM) enable fluorescence microscopy super-resolution: The overcoming of the resolution barrier imposed by the diffraction of light. These techniques are based on acquiring hundreds or thousands of images of single molecules, locating them and reconstructing a higher-resolution image from the high-precision localizations. These methods generally imply a considerable trade-off between imaging speed and resolution, limiting their applicability to high-throughput workflows. Recent advancements in scientific Complementary Metal-Oxide Semiconductor (sCMOS) camera sensors and localization algorithms reduce the temporal requirements for SMLM, pushing it toward high-throughput microscopy. Here we outline the decisions researchers face when considering how to adapt hardware on a new system for sCMOS sensors with high-throughput in mind.
%0 Journal Article
%1 Almada2015
%A Almada, Pedro
%A Culley, Siân
%A Henriques, Ricardo
%D 2015
%I Elsevier Inc.
%J Methods
%K hardware microscopy sCMOS smlm
%P 109--121
%R 10.1016/j.ymeth.2015.06.004
%T PALM and STORM: Into large fields and high-throughput microscopy with sCMOS detectors
%U http://dx.doi.org/10.1016/j.ymeth.2015.06.004
%V 88
%X Single Molecule Localization Microscopy (SMLM) techniques such as Photo-Activation Localization Microscopy (PALM) and Stochastic Optical Reconstruction Microscopy (STORM) enable fluorescence microscopy super-resolution: The overcoming of the resolution barrier imposed by the diffraction of light. These techniques are based on acquiring hundreds or thousands of images of single molecules, locating them and reconstructing a higher-resolution image from the high-precision localizations. These methods generally imply a considerable trade-off between imaging speed and resolution, limiting their applicability to high-throughput workflows. Recent advancements in scientific Complementary Metal-Oxide Semiconductor (sCMOS) camera sensors and localization algorithms reduce the temporal requirements for SMLM, pushing it toward high-throughput microscopy. Here we outline the decisions researchers face when considering how to adapt hardware on a new system for sCMOS sensors with high-throughput in mind.
%@ 1095-9130 (Electronic)$\backslash$r1046-2023 (Linking)
@article{Almada2015,
abstract = {Single Molecule Localization Microscopy (SMLM) techniques such as Photo-Activation Localization Microscopy (PALM) and Stochastic Optical Reconstruction Microscopy (STORM) enable fluorescence microscopy super-resolution: The overcoming of the resolution barrier imposed by the diffraction of light. These techniques are based on acquiring hundreds or thousands of images of single molecules, locating them and reconstructing a higher-resolution image from the high-precision localizations. These methods generally imply a considerable trade-off between imaging speed and resolution, limiting their applicability to high-throughput workflows. Recent advancements in scientific Complementary Metal-Oxide Semiconductor (sCMOS) camera sensors and localization algorithms reduce the temporal requirements for SMLM, pushing it toward high-throughput microscopy. Here we outline the decisions researchers face when considering how to adapt hardware on a new system for sCMOS sensors with high-throughput in mind.},
added-at = {2020-03-23T21:12:34.000+0100},
author = {Almada, Pedro and Culley, Si{\^{a}}n and Henriques, Ricardo},
biburl = {https://www.bibsonomy.org/bibtex/203241746bfd952770eecefa83d3b9846/kfriedl},
doi = {10.1016/j.ymeth.2015.06.004},
file = {:C$\backslash$:/Users/Karoline/Documents/Abbelight/Literatur/1-s2.0-S1046202315002455-main (1).pdf:pdf},
interhash = {7a863690f4f81c71c7b58b7ed4fc6fb5},
intrahash = {03241746bfd952770eecefa83d3b9846},
isbn = {1095-9130 (Electronic)$\backslash$r1046-2023 (Linking)},
issn = {10959130},
journal = {Methods},
keywords = {hardware microscopy sCMOS smlm},
pages = {109--121},
pmid = {26079924},
publisher = {Elsevier Inc.},
timestamp = {2020-03-23T21:58:46.000+0100},
title = {{PALM and STORM: Into large fields and high-throughput microscopy with sCMOS detectors}},
url = {http://dx.doi.org/10.1016/j.ymeth.2015.06.004},
volume = 88,
year = 2015
}