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- W2950874670 abstract "Super-resolution microscopy methods (e.g.STORM or PALM imaging) have becomeessential tools in biology, opening up a va-riety of new questions that were previouslyinaccessible with standard light microscopymethods. In this paper we develop newBayesian image processing methods thatextend the reach of super-resolution mi-croscopy even further. Our method couplesvariational inference techniques with a datasummarization based on Laplace approxi-mation to ensure computational scalability.Our formulation makes it straightforwardto incorporate prior information about theunderlying sample to further improve ac-curacy. The proposed method obtains dra-matic resolution improvements over previ-ous methods while retaining computationaltractability." @default.
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- W2950874670 date "2017-04-10" @default.
- W2950874670 modified "2023-09-28" @default.
- W2950874670 title "Scalable Variational Inference for Super Resolution Microscopy" @default.
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