| L0 constrained sparse reconstruction for multi-slice helical CT reconstruction. | |
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MedLine Citation:
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PMID: 21285478 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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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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Authors:
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Yining Hu; Lizhe Xie; Limin Luo; Jean Claude Nunes; Christine Toumoulin |
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Publication Detail:
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Type: Journal Article; Research Support, Non-U.S. Gov't Date: 2011-02-01 |
Journal Detail:
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Title: Physics in medicine and biology Volume: 56 ISSN: 1361-6560 ISO Abbreviation: Phys Med Biol Publication Date: 2011 Feb |
Date Detail:
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Created Date: 2011-02-02 Completed Date: 2011-05-19 Revised Date: 2012-09-18 |
Medline Journal Info:
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Nlm Unique ID: 0401220 Medline TA: Phys Med Biol Country: England |
Other Details:
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Languages: eng Pagination: 1173-89 Citation Subset: IM |
Affiliation:
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Laboratory of Image Science and Technology (LIST), South East University, Nanjing, People's Republic of China. |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Algorithms Humans Image Processing, Computer-Assisted / methods* Models, Theoretical Phantoms, Imaging Rotation Tomography, Spiral Computed / methods* |
| Comments/Corrections | |
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