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2014 22nd International Conference on Pattern Recognition

DOI: 10.1109/icpr.2014.159

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Three-Dimensional Deconvolution of Wide Field Microscopy with Sparse Priors: Application to Zebrafish Imagery

Proceedings article published in 2014 by Bo Dong, Ling Shao, Alejandro F. Frangi, Oliver Bandmann, Marc Da Costa ORCID
This paper is available in a repository.
This paper is available in a repository.

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Data provided by SHERPA/RoMEO

Abstract

Zebrafish, as a popular experimental model or-ganism, has been frequently used in biomedical research. For observing, analysing and recording labelled transparent features in zebrafish images, it is often efficient and convenient to adopt the fluorescence microscopy. However, the acquired z-stack im-ages are always blurred, which makes deblurring/deconvolution critical for further image analysis. In this paper, we propose a Bayesian Maximum a-Posteriori (MAP) method with the sparse image priors to solve three-dimensional (3D) deconvolution prob-lem for Wide Field (WF) fluorescence microscopy images from zebrafish embryos. The novel sparse image priors include a global Hyper-Laplacian model and a local smooth region mask. These two kinds of prior are deployed for preserving sharp edges and suppressing ringing artifacts, respectively. Both synthetic and real WF fluorescent zebrafish embryo data are used for evaluation. Experimental results demonstrate the potential applicability of the proposed method for 3D fluorescence microscopy images, compared with state-of-the-art 3D deconvolution algorithms.