Efficient Bayesian-based multiview deconvolution

A graphical processing unit implementation of an efficient Bayesian-based multiview deconvolution method brings the resolution and contrast advantages of multiview deconvolution to more users of light-sheet fluorescence microscopy. Light-sheet fluorescence microscopy is able to image large specimens...

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Veröffentlicht in:Nature methods 2014-06, Vol.11 (6), p.645-648
Hauptverfasser: Preibisch, Stephan, Amat, Fernando, Stamataki, Evangelia, Sarov, Mihail, Singer, Robert H, Myers, Eugene, Tomancak, Pavel
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Sprache:eng
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Zusammenfassung:A graphical processing unit implementation of an efficient Bayesian-based multiview deconvolution method brings the resolution and contrast advantages of multiview deconvolution to more users of light-sheet fluorescence microscopy. Light-sheet fluorescence microscopy is able to image large specimens with high resolution by capturing the samples from multiple angles. Multiview deconvolution can substantially improve the resolution and contrast of the images, but its application has been limited owing to the large size of the data sets. Here we present a Bayesian-based derivation of multiview deconvolution that drastically improves the convergence time, and we provide a fast implementation using graphics hardware.
ISSN:1548-7091
1548-7105
DOI:10.1038/nmeth.2929