[1] Zhou Zhengdong, Yu Zili, Zhang Wenwen, Guan Shaolin, et al. Investigation of prior image constrained compressed sensing-basedspectral X-ray CT image reconstruction [J]. Journal of Southeast University (English Edition), 2016, 32 (4): 420-425. [doi:10.3969/j.issn.1003-7985.2016.04.005]

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Investigation of prior image constrained compressed sensing-basedspectral X-ray CT image reconstruction()

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

32

Issue:

2016 4

Page:

420-425

Research Field:

Computer Science and Engineering

Publishing date:

2016-12-20

Info

Title:

Investigation of prior image constrained compressed sensing-basedspectral X-ray CT image reconstruction

Author(s):

Zhou Zhengdong;  Yu Zili;  Zhang Wenwen;  Guan Shaolin

Department of Nuclear Science and Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

Keywords:

spectral X-ray CT;  prior image;  compressed sensing;  optimization algorithm;  image reconstruction

PACS:

TP391;R318

DOI:

10.3969/j.issn.1003-7985.2016.04.005

Abstract:

To improve spectral X-ray CT reconstructed image quality, the energy-weighted reconstructed image x^W_bins and the separable paraboloidal surrogates(SPS)algorithm are proposed for the prior image constrained compressed sensing(PICCS)-based spectral X-ray CT image reconstruction. The PICCS-based image reconstruction takes advantage of the compressed sensing theory, a prior image and an optimization algorithm to improve the image quality of CT reconstructions. To evaluate the performance of the proposed method, three optimization algorithms and three prior images are employed and compared in terms of reconstruction accuracy and noise characteristics of the reconstructed images in each energy bin. The experimental simulation results show that the image x^W_bins is the best as the prior image in general with respect to the three optimization algorithms; and the SPS algorithm offers the best performance for the simulated phantom with respect to the three prior images. Compared with filtered back-projection(FBP), the PICCS via the SPS algorithm and x^W_bins as the prior image can offer the noise reduction in the reconstructed images up to 80.46%, 82.51%, 88.08% in each energy bin, respectively. Meanwhile, the root-mean-squared error in each energy bin is decreased by 15.02%, 18.15%, 34.11% and the correlation coefficient is increased by 9.98%, 11.38%, 15.94%, respectively.

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Memo

Memo:

Biography: Zhou Zhengdong(1969—), male, doctor, associate professor, zzd_msc@nuaa.edu.cn.
Foundation items: The National Natural Science Foundation of China(No.51575256), the Fundamental Research Funds for the Central Universities(No.NP2015101, XZA16003), the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD).
Citation: Zhou Zhengdong, Yu Zili, Zhang Wenwen, et al. Investigation of prior image constrained compressed sensing-based spectral X-ray CT image reconstruction[J].Journal of Southeast University(English Edition), 2016, 32(4):420-425.DOI:10.3969/j.issn.1003-7985.2016.04.005.

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