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Hybrid reconstruction algorithm for computed tomography based on diagonal total variation

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Abstract

Inspired by total variation (TV), this paper represents a new iterative algorithm based on diagonal total variation (DTV) to address the computed tomography image reconstruction problem. To improve the quality of a reconstructed image, we used DTV to sparsely represent images when iterative convergence of the reconstructed algorithm with TV-constraint had no effect during the reconstruction process. To investigate our proposed algorithm, the numerical and experimental studies were performed, and root-mean-square error (RMSE) and structure similarity (SSIM) were used to evaluate the reconstructed image quality. The results demonstrated that the proposed method could effectively reduce noise, suppress artifacts, and reconstruct high-quality image from incomplete projection data.

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Authors and Affiliations

  1. Key Laboratory of Optoelectronic Technology and Systems, Ministry of Education, Chongqing University, Chongqing, 400044, China

    Lu-Zhen Deng, Peng He, Shang-Hai Jiang, Mian-Yi Chen, Biao Wei & Peng Feng

  2. Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA

    Lu-Zhen Deng

  3. ICT NDT Engineering Research Center, Ministry of Education, Chongqing University, Chongqing, 400044, China

    Peng He, Biao Wei & Peng Feng

  4. Collaborative Innovation Center for Brain Science, Chongqing University, Chongqing, 400044, China

    Peng He, Biao Wei & Peng Feng

Authors
  1. Lu-Zhen Deng
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  2. Peng He
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  3. Shang-Hai Jiang
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  4. Mian-Yi Chen
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  5. Biao Wei
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  6. Peng Feng
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Corresponding authors

Correspondence to Peng He or Peng Feng.

Additional information

This work was supported in part by the National Natural Science Foundation of China (No. 61401049), the Chongqing Foundation and Frontier Research Project (Nos. cstc2016jcyjA0473, cstc2013jcyjA0763), the Graduate Scientific Research and Innovation Foundation of Chongqing, China (No. CYB16044), the Strategic Industry Key Generic Technology Innovation Project of Chongqing (No. cstc2015zdcy-ztzxX0002), China Scholarship Council, and the Fundamental Research Funds for the Central Universities Nos. CDJZR14125501, 106112016CDJXY120003, 10611CDJXZ238826.

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Deng, LZ., He, P., Jiang, SH. et al. Hybrid reconstruction algorithm for computed tomography based on diagonal total variation. NUCL SCI TECH 29, 45 (2018). https://doi.org/10.1007/s41365-018-0376-2

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  • DOI: https://doi.org/10.1007/s41365-018-0376-2

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