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Computer Optics, 2021, Volume 45, Issue 3, Pages 418–426
DOI: https://doi.org/10.18287/2412-6179-CO-825
(Mi co925)
 

This article is cited in 5 scientific papers (total in 5 papers)

IMAGE PROCESSING, PATTERN RECOGNITION

Solving the boundary artifact for the enhanced deconvolution algorithm SUPPOSe applied to fluorescence microscopy

M. Toscania, S. Martinezb

a Laboratorio de Fotónica, Instituto de Ingeniería Biomédica, FI-UBA, CONICET, Buenos Aires, Argentina
b Departamento de Matemática, FCEyN-UBA, IMAS, CONICET, Buenos Aires, Argentina
References:
Abstract: The SUPPOSe enhanced deconvolution algorithm relies in assuming that the image source can be described by an incoherent superposition of virtual point sources of equal intensity and finding the number and position of such virtual sources. In this work we describe the recent advances in the implementation of the method to gain resolution and remove artifacts due to the presence of fluorescent molecules close enough to the image frame boundary. The method was modified removing the invariant used before given by the product of the flux of the virtual sources times the number of virtual sources, and replacing it by a new invariant given by the total flux within the frame, thus allowing the location of virtual sources outside the frame but contributing to the signal inside the frame.
Keywords: deconvolution, fluorescence, microscopy, boundary, artifact.
Funding agency
The work was partially funded by Agencia Nacional de Promoción Científica y Tecnológica, PICT 2015-1523; Universidad de Buenos Aires, ubacyt2018 20020170100137BA; and AFOSR, FA9550-18-1-0470 P00001.
Received: 27.10.2020
Accepted: 16.02.2021
Document Type: Article
Language: English
Citation: M. Toscani, S. Martinez, “Solving the boundary artifact for the enhanced deconvolution algorithm SUPPOSe applied to fluorescence microscopy”, Computer Optics, 45:3 (2021), 418–426
Citation in format AMSBIB
\Bibitem{TosMar21}
\by M.~Toscani, S.~Martinez
\paper Solving the boundary artifact for the enhanced deconvolution algorithm SUPPOSe applied to fluorescence microscopy
\jour Computer Optics
\yr 2021
\vol 45
\issue 3
\pages 418--426
\mathnet{http://mi.mathnet.ru/co925}
\crossref{https://doi.org/10.18287/2412-6179-CO-825}
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  • https://www.mathnet.ru/eng/co925
  • https://www.mathnet.ru/eng/co/v45/i3/p418
  • This publication is cited in the following 5 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Computer Optics
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