A hierarchical reconstruction of x-ray phase tomography based on transferred non-local structural features

Ziling Wu; Ting Yang; Ling Li; Yunhui Zhu

doi:10.1117/12.2519055

14 May 2019 A hierarchical reconstruction of x-ray phase tomography based on transferred non-local structural features

Ziling Wu, Ting Yang, Ling Li, Yunhui Zhu

Proceedings Volume 10999, Anomaly Detection and Imaging with X-Rays (ADIX) IV; 109990N (2019) https://doi.org/10.1117/12.2519055
Event: SPIE Defense + Commercial Sensing, 2019, Baltimore, MD, United States

Abstract

X-ray computed tomography has been recently applied to capture the dynamic behaviors of complex material systems in 4D. The dynamic 3D acquisition, however, usually leads to insufficient data acquisition with low-dose X-ray radiation and limited-angle projections. A high-fidelity CT reconstruction is challenging based on the severely limited acquisition. While prior constraint, such as local smoothness, can improve the quality of reconstructions, a more general reconstruction strategy to include structural features on a range of different scales proves to yield better reconstruction results and are more adaptive to complex structured materials. In this work, we develop the hierarchical synthesis network to establish structural priors for sparse-view CT reconstruction, which achieves high-fidelity with an improved computation efficiency. We found that the established knowledge of structural priors on each different scale can be independently transferred to sparse-view CT reconstruction under different conditions, enabling the transfer of non-local features into the reconstruction of a phase tomography application.

Conference Presentation

Citation Download Citation

Ziling Wu, Ting Yang, Ling Li, and Yunhui Zhu "A hierarchical reconstruction of x-ray phase tomography based on transferred non-local structural features", Proc. SPIE 10999, Anomaly Detection and Imaging with X-Rays (ADIX) IV, 109990N (14 May 2019); https://doi.org/10.1117/12.2519055

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