Nonlinear image restoration methods for marker extraction in 3D fluorescent microscopy

Aleh Kryvanos; Juergen Hesser; Gabriele Steidl

doi:10.1117/12.586909

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11 March 2005 Nonlinear image restoration methods for marker extraction in 3D fluorescent microscopy

Aleh Kryvanos; Juergen Hesser; Gabriele Steidl

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Proceedings Volume 5674, Computational Imaging III; (2005) https://doi.org/10.1117/12.586909
Event: Electronic Imaging 2005, 2005, San Jose, California, United States

Abstract

Localization of biological markers in images obtained by fluorescent microscopy is a relevant problem in biological research. Due to blurring from imaging and noise, the analysis of supra-molecular structures can be improved by image restoration. In this paper, we compare various deblurring algorithms with and without regularization. In the first group we consider the EM (Expectation Maximization) and the JVC (Jansson-van-Cittert) algorithms and examine the effect of the Tikhonov and the TV (Total Variation) regularization in the second group. The last approach uses the I-divergence as similarity measure. As solution method for our new I-divergence--TV model we propose a non-linear projective conjugate gradient algorithm with inexact linear search. Optimal regularization parameters were found by the shape analysis of corresponding L-curves.

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Aleh Kryvanos, Juergen Hesser, and Gabriele Steidl "Nonlinear image restoration methods for marker extraction in 3D fluorescent microscopy", Proc. SPIE 5674, Computational Imaging III, (11 March 2005); https://doi.org/10.1117/12.586909

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