期刊
OPTICS EXPRESS
卷 30, 期 11, 页码 18219-18237出版社
Optica Publishing Group
DOI: 10.1364/OE.456184
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资金
- National Natural Science Foundation of China [61871351, 61971381, 62122070]
This paper proposes a statistical iterative spectral computed tomography (CT) imaging method based on blind separation of polychromatic projections to improve the accuracy of narrow-energy-width image decomposition. Experimental results show that the novel algorithm obtains more accurate narrow-energy-width images compared to state-of-the-art methods.
Spectral computed tomography (CT) can provide narrow-energy-width reconstructed images, thereby suppressing beam hardening artifacts and providing rich attenuation information for component characterization. We propose a statistical iterative spectral CT imaging method based on blind separation of polychromatic projections to improve the accuracy of narrow-energy-width image decomposition. For direct inversion in blind scenarios, we introduce the system matrix into the X-ray multispectral forward model to reduce indirect errors. A constrained optimization problem with edge-preserving regularization is established and decomposed into two sub-problems to be alternately solved. Experiments indicate that the novel algorithm obtains more accurate narrow-energy-width images than the state-of-the-art method. (C) 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement
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