Image reconstruction in CT from limited-angle projections

Dou Li; Shanshan Wang; Zemin Cai; Dong Liang; Jianhua Luo

doi:10.1117/12.2524246

6 May 2019 Image reconstruction in CT from limited-angle projections

Dou Li, Shanshan Wang, Zemin Cai, Dong Liang, Jianhua Luo

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.

Citation Download Citation

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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