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Efficient Bayesian-based multiview deconvolution.


ABSTRACT: 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.

SUBMITTER: Preibisch S 

PROVIDER: S-EPMC4153441 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature

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Efficient Bayesian-based multiview deconvolution.

Preibisch Stephan S   Amat Fernando F   Stamataki Evangelia E   Sarov Mihail M   Singer Robert H RH   Myers Eugene E   Tomancak Pavel P  

Nature methods 20140420 6


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. ...[more]

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