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Journal of Biomedical Optics

Optical imaging of fluorescent carbon biomarkers using artificial neural networks
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Paper Abstract

The principle possibility of extraction of fluorescence of nanoparticles in the presence of background autofluorescence of a biological environment using neural network algorithms is demonstrated. It is shown that the methods used allow detection of carbon nanoparticles fluorescence against the background of the autofluorescence of egg white with a sufficiently low concentration detection threshold (not more than 2  μg/ml for carbon dots and 3  μg/ml for nanodiamonds). It was also shown that the use of the input data compression can further improve the accuracy of solving the inverse problem by 1.5 times.

Paper Details

Date Published: 14 November 2014
PDF: 9 pages
J. Biomed. Opt. 19(11) 117007 doi: 10.1117/1.JBO.19.11.117007
Published in: Journal of Biomedical Optics Volume 19, Issue 11
Show Author Affiliations
Tatiana A. Dolenko, Lomonosov Moscow State Univ. (Russia)
Sergey A. Burikov, Lomonosov Moscow State Univ. (Russia)
Alexey M. Vervald, Lomonosov Moscow State Univ. (Russia)
Igor I. Vlasov, A. M. Prokhorov General Physics Institute (Russia)
National Research Nuclear Univ. MEPhI (Russia)
Sergey A. Dolenko, Lomonosov Moscow State Univ. (Russia)
Kirill A. Laptinskiy, Lomonosov Moscow State Univ. (Russia)
Jessica M. Rosenholm, Åbo Akademi Univ. (Finland)
Olga A. Shenderova, Adámas Nanotechnologies, Inc. (United States)

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