BIOMEDICAL IMAGING GROUP (BIG)
Laboratoire d'imagerie biomédicale (LIB)

Deconvolution of 3D Fluorescence Micrographs with Automatic Risk Minimization

S. Ramani, C. Vonesch, M. Unser

Proceedings of the Fifth IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI'08), Paris, French Republic, May 14-17, 2008, pp. 732–735.

We investigate the problem of automatic tuning of a deconvolution algorithm for three-dimensional (3D) fluorescence microscopy; specifically, the selection of the regularization parameter λ. For this, we consider a realistic noise model for data obtained from a CCD detector: Poisson photon-counting noise plus Gaussian read-out noise. Based on this model, we develop a new risk measure which unbiasedly estimates the original mean-squared-error of the deconvolved signal estimate. We then show how to use this risk estimate to optimize the regularization parameter for Tikhonov-type deconvolution algorithms. We present experimental results on simulated data and numerically demonstrate the validity of the proposed risk measure. We also present results for real 3D microscopy data. 

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AUTHOR="Ramani, S. and Vonesch, C. and Unser, M.",
TITLE="Deconvolution of {3D} Fluorescence Micrographs with Automatic
	Risk Minimization",
BOOKTITLE="Proceedings of the Fifth {IEEE} International Symposium on
	Biomedical Imaging: {F}rom Nano to Macro ({ISBI'08})",
YEAR="2008",
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series="",
pages="732--735",
address="Paris, French Republic",
month="May 14-17,",
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