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Article Dans Une Revue Physics in Medicine and Biology Année : 2011

L0 constrained sparse reconstruction for multi-slice helical CT reconstruction.

Résumé

In this paper, we present a Bayesian maximum a posteriori method for multi-slice helical CT reconstruction based on an L0-norm prior. It makes use of a very low number of projections. A set of surrogate potential functions is used to successively approximate the L0-norm function while generating the prior and to accelerate the convergence speed. Simulation results show that the proposed method provides high quality reconstructions with highly sparse sampled noise-free projections. In the presence of noise, the reconstruction quality is still significantly better than the reconstructions obtained with L1-norm or L2-norm priors.
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Dates et versions

inserm-00566886 , version 1 (17-02-2011)

Identifiants

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Yining Hu, Lizhe Xie, Limin M. Luo, Jean Claude Nunes, Christine Toumoulin. L0 constrained sparse reconstruction for multi-slice helical CT reconstruction.. Physics in Medicine and Biology, 2011, 56 (4), pp.1173-89. ⟨10.1088/0031-9155/56/4/018⟩. ⟨inserm-00566886⟩
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