Multiple signal classification algorithm for super-resolution fluorescence microscopy View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2016-12-09

AUTHORS

Krishna Agarwal, Radek Macháň

ABSTRACT

Single-molecule localization techniques are restricted by long acquisition and computational times, or the need of special fluorophores or biologically toxic photochemical environments. Here we propose a statistical super-resolution technique of wide-field fluorescence microscopy we call the multiple signal classification algorithm which has several advantages. It provides resolution down to at least 50 nm, requires fewer frames and lower excitation power and works even at high fluorophore concentrations. Further, it works with any fluorophore that exhibits blinking on the timescale of the recording. The multiple signal classification algorithm shows comparable or better performance in comparison with single-molecule localization techniques and four contemporary statistical super-resolution methods for experiments of in vitro actin filaments and other independently acquired experimental data sets. We also demonstrate super-resolution at timescales of 245 ms (using 49 frames acquired at 200 frames per second) in samples of live-cell microtubules and live-cell actin filaments imaged without imaging buffers. More... »

PAGES

13752

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/ncomms13752

DOI

http://dx.doi.org/10.1038/ncomms13752

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1005407822

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/27934858


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