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Efficient Bayesian-based multiview deconvolution
DOI:10.1038/NMETH.2929.png)
Abstract
En 中文
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.
Keywords:
LIGHT-SHEET MICROSCOPY
PLANE ILLUMINATION MICROSCOPY
RECONSTRUCTION
RESTORATION
RESOLUTION
PLATFORM
DEEP
Journal
IF:
32.1
Papers:
7.2K
Citations:
12.7W
Organization
Cited Papers
High-resolution three-dimensional imaging of large specimens with light sheet-based microscopy
NATURE METHODS
IF32.1

