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6 May 2019 Image reconstruction in CT from limited-angle projections
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Proceedings Volume 11069, Tenth International Conference on Graphics and Image Processing (ICGIP 2018); 1106916 (2019) https://doi.org/10.1117/12.2524246
Event: Tenth International Conference on Graphic and Image Processing (ICGIP 2018), 2018, Chengdu, China
Abstract
Limited-angle tomography has gained much interest in late years Nevertheless, image reconstruction from incomplete projections is a classic ill-posed issue in the field of computational imaging. In this paper, we propose a scheme based on the sparsifying operators and approximation of ℓ0-minimization. Our framework includes two main components, one for a sparsifying operator, and one for learning the scheme parameters using ℓ0-minimization from insufficient computed tomography data. Thus, the proposed scheme is capable of recovering high quality reconstructions at a range of angles and noise. Compared to the total-variation (TV) regularized reconstruction scheme, σ-u scheme and ATV (Anisotropic Total Variation) scheme, validations using Shepp-Logan phantom computed tomography data demonstrate the significant improvements in SNR and suppressed noise and artifacts.
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Dou Li, Shanshan Wang, Zemin Cai, Dong Liang, and Jianhua Luo "Image reconstruction in CT from limited-angle projections", Proc. SPIE 11069, Tenth International Conference on Graphics and Image Processing (ICGIP 2018), 1106916 (6 May 2019); https://doi.org/10.1117/12.2524246
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