Binary Tomography Reconstructions With Stochastic Level-Set Methods

doi:10.1109/LSP.2014.2375511

2015-07-01

PRE

DOI：10.1109/LSP.2014.2375511

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摘要

En 中文

In this work, we propose a stochastic level-set method to reconstruct binary tomography cross-sections from few projections. A first reconstruction image is obtained with a level-set regularization method. The reconstruction is then refined with a stochastic partial differential equation based on a Stratanovitch formulation. The reconstruction results are compared with the ones obtained with the classical simulated annealing method. The methods are tested on a complex bone mu - CT cross-section for different noise levels and number of projections. The best reconstruction results are obtained with the stochastic level set-method.

Keyword:

Binary tomography

inverse problems

level-set

x-ray imaging

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期刊

IEEE Signal Processing Magazine

IF:

9.6

论文数:

1.1W

被引数:

1.7W

机构

institut national des sciences appliquees de lyon - insa lyon

学者数:

6.1K

论文数: 4.7K

被引数: 2

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