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Efficient Bayesian-based multiview deconvolution
by
Myers, Eugene
, Amat, Fernando
, Singer, Robert H
, Tomancak, Pavel
, Preibisch, Stephan
, Sarov, Mihail
, Stamataki, Evangelia
in
14/63
/ 631/114/1564
/ 631/114/794
/ 631/1647/245/2225
/ 631/1647/328/2237
/ 64/11
/ 64/24
/ Algorithms
/ Analysis
/ Bayes Theorem
/ Bayesian analysis
/ Bayesian statistical decision theory
/ Bioinformatics
/ Biological Microscopy
/ Biological Techniques
/ Biomedical Engineering/Biotechnology
/ brief-communication
/ Diagnostic imaging
/ Fluorescence
/ Fluorescence microscopy
/ Image Processing, Computer-Assisted
/ Life Sciences
/ Methods
/ Microscopy
/ Microscopy, Fluorescence - instrumentation
/ Microscopy, Fluorescence - methods
/ Proteomics
2014
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Efficient Bayesian-based multiview deconvolution
by
Myers, Eugene
, Amat, Fernando
, Singer, Robert H
, Tomancak, Pavel
, Preibisch, Stephan
, Sarov, Mihail
, Stamataki, Evangelia
in
14/63
/ 631/114/1564
/ 631/114/794
/ 631/1647/245/2225
/ 631/1647/328/2237
/ 64/11
/ 64/24
/ Algorithms
/ Analysis
/ Bayes Theorem
/ Bayesian analysis
/ Bayesian statistical decision theory
/ Bioinformatics
/ Biological Microscopy
/ Biological Techniques
/ Biomedical Engineering/Biotechnology
/ brief-communication
/ Diagnostic imaging
/ Fluorescence
/ Fluorescence microscopy
/ Image Processing, Computer-Assisted
/ Life Sciences
/ Methods
/ Microscopy
/ Microscopy, Fluorescence - instrumentation
/ Microscopy, Fluorescence - methods
/ Proteomics
2014
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Do you wish to request the book?
Efficient Bayesian-based multiview deconvolution
by
Myers, Eugene
, Amat, Fernando
, Singer, Robert H
, Tomancak, Pavel
, Preibisch, Stephan
, Sarov, Mihail
, Stamataki, Evangelia
in
14/63
/ 631/114/1564
/ 631/114/794
/ 631/1647/245/2225
/ 631/1647/328/2237
/ 64/11
/ 64/24
/ Algorithms
/ Analysis
/ Bayes Theorem
/ Bayesian analysis
/ Bayesian statistical decision theory
/ Bioinformatics
/ Biological Microscopy
/ Biological Techniques
/ Biomedical Engineering/Biotechnology
/ brief-communication
/ Diagnostic imaging
/ Fluorescence
/ Fluorescence microscopy
/ Image Processing, Computer-Assisted
/ Life Sciences
/ Methods
/ Microscopy
/ Microscopy, Fluorescence - instrumentation
/ Microscopy, Fluorescence - methods
/ Proteomics
2014
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Journal Article
Efficient Bayesian-based multiview deconvolution
2014
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Overview
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.
Publisher
Nature Publishing Group US,Nature Publishing Group
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