Open AccessA modified discrete tomography for improving the reconstruction of unknown multi‐gray‐level material in the `missing wedge' situation
Author(s) -
Liu Jianhong,
Liang Zhiting,
Guan Yong,
Wei Wenbin,
Bai Haobo,
Chen Liang,
Liu Gang,
Tian Yangchao
Publication year - 2018
Publication title -
journal of synchrotron radiation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.172
H-Index - 99
ISSN - 1600-5775
DOI - 10.1107/s1600577518013681
Subject(s) - wedge (geometry) , missing data , tomography , tomographic reconstruction , computer science , algorithm , iterative reconstruction , computed tomography , algebraic number , artificial intelligence , mathematics , geometry , physics , mathematical analysis , optics , machine learning , medicine , radiology
Full angular rotational projections cannot always be acquired in tomographic reconstructions because of the limited space in the experimental setup, leading to the `missing wedge' situation. In this paper, a recovering `missing wedge' discrete algebraic reconstruction technique algorithm (rmwDART) has been proposed to solve the `missing wedge' problem and improve the quality of the three‐dimensional reconstruction without prior knowledge of the material component's number or the material's values. By using oversegmentation, boundary extraction and mathematical morphological operations, `missing wedge' artifact areas can be located. Then, in the iteration process, by updating the located areas and regions, high‐quality reconstructions can be obtained from the simulations, and the reconstructed images based on the rmwDART algorithm can be obtained from soft X‐ray nano‐computed tomography experiments. The results showed that there is the potential for discrete tomography.