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Acta Optica Sinica, Volume. 38, Issue 1, 0111003(2018)

Improved Stochastic CT Reconstruction Based on Particle Swarm Optimization for Limited-Angle Sparse Projection Data

Hongxia Gao1, Lan Luo1, Yinghao Luo1、*, Zhanhong Chen1, and Ge Ma2
Author Affiliations
  • 1School of Automation Science and Engineering, South China University of Technology, Guangzhou, Guangdong 510640, China
  • 2School of Mechanical and Electric Engineering, Guangzhou University, Guangzhou, Guangdong 510006, China
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    AbstractGet PDF(in Chinese)
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    Figures & Tables(14)
    Discrete projection process of X rays

    Fig. 1. Discrete projection process of X rays

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    Illustration of incomplete projection data. (a) Limited-angle data; (b) sparse view data; (c) limited-angle sparse view data

    Fig. 2. Illustration of incomplete projection data. (a) Limited-angle data; (b) sparse view data; (c) limited-angle sparse view data

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    Reconstruction results from noise-free Shepp sparse Logan projection data. (a) Original image of Shepp Logan; (b) L2-TV algorithm; (c) SAG algorithm; (d) POCS-TV algorithm; (e) PSO algorithm; (f) proposed algorithm

    Fig. 3. Reconstruction results from noise-free Shepp sparse Logan projection data. (a) Original image of Shepp Logan; (b) L2-TV algorithm; (c) SAG algorithm; (d) POCS-TV algorithm; (e) PSO algorithm; (f) proposed algorithm

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    Reconstruction results from noise-free Forbild Head sparse projection data. (a) Original image of Forbild Head; (b) L2-TV algorithm; (c) SAG algorithm; (d) POCS-TV algorithm; (e) PSO algorithm; (f) proposed algorithm

    Fig. 4. Reconstruction results from noise-free Forbild Head sparse projection data. (a) Original image of Forbild Head; (b) L2-TV algorithm; (c) SAG algorithm; (d) POCS-TV algorithm; (e) PSO algorithm; (f) proposed algorithm

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    Comparison of horizontal (a) and vertical (b) profiles with noise-free Shepp Logan projection data

    Fig. 5. Comparison of horizontal (a) and vertical (b) profiles with noise-free Shepp Logan projection data

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    Comparison of horizontal (a) and vertical (b) profiles with noise-free Forbild Head projection data

    Fig. 6. Comparison of horizontal (a) and vertical (b) profiles with noise-free Forbild Head projection data

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    Reconstruction results from Shepp Logan projection data with Gaussian noise. (a) Original image of Shepp Logan; (b) L2-TV algorithm; (c) SAG algorithm; (d) POCS-TV algorithm; (e) PSO algorithm; (f) proposed algorithm

    Fig. 7. Reconstruction results from Shepp Logan projection data with Gaussian noise. (a) Original image of Shepp Logan; (b) L2-TV algorithm; (c) SAG algorithm; (d) POCS-TV algorithm; (e) PSO algorithm; (f) proposed algorithm

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    Reconstruction results from Forbild Head projection data with Gaussian noise. (a) Original image of Forbild Head; (b) L2-TV algorithm; (c) SAG algorithm; (d) POCS-TV algorithm; (e) PSO algorithm; (f) proposed algorithm

    Fig. 8. Reconstruction results from Forbild Head projection data with Gaussian noise. (a) Original image of Forbild Head; (b) L2-TV algorithm; (c) SAG algorithm; (d) POCS-TV algorithm; (e) PSO algorithm; (f) proposed algorithm

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    Comparison of horizontal (a) and vertical (b) profiles with noisy Shepp Logan projection data

    Fig. 9. Comparison of horizontal (a) and vertical (b) profiles with noisy Shepp Logan projection data

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    Comparison of horizontal (a) and vertical (b) profiles with noisy Forbild Head projection data

    Fig. 10. Comparison of horizontal (a) and vertical (b) profiles with noisy Forbild Head projection data

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    Reconstruction error curves with the change of iteration number of different algorithms. (a) Noise-free Shepp Logan projection data; (b) noise-free Forbild Head projection data; (c) noisy Shepp Logan projection data; (d) noisy Forbild Head projection data

    Fig. 11. Reconstruction error curves with the change of iteration number of different algorithms. (a) Noise-free Shepp Logan projection data; (b) noise-free Forbild Head projection data; (c) noisy Shepp Logan projection data; (d) noisy Forbild Head projection data

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    Reconstruction error curves with the change of iteration time of different algorithms. (a) Noise-free Shepp Logan projection data; (b) noise-free Forbild Head projection data; (c) noisy Shepp Logan projection data; (d) noisy Forbild Head projection data

    Fig. 12. Reconstruction error curves with the change of iteration time of different algorithms. (a) Noise-free Shepp Logan projection data; (b) noise-free Forbild Head projection data; (c) noisy Shepp Logan projection data; (d) noisy Forbild Head projection data

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    • Table 1. Comparison of reconstruction error with noise-free projection data

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      Table 1. Comparison of reconstruction error with noise-free projection data

      ImageL2-TV algorithmSAG algorithmPOCS-TV algorithmPSO algorithmProposed algorithm
      Shepp Logan24.56745.0062197.47773340.60080.0439
      Forbild Head26.99560.0833236.73073515.62330.0379

    • Table 2. Comparison of reconstruction error with noisy projection data

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      Table 2. Comparison of reconstruction error with noisy projection data

      ImageL2-TV algorithmSAG algorithmPOCS-TV algorithmPSO algorithmProposed algorithm
      Shepp Logan28.273138.2937215.84843363.236926.1932
      Forbild Head41.378845.8357251.28323380.026630.1645
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    Hongxia Gao, Lan Luo, Yinghao Luo, Zhanhong Chen, Ge Ma. Improved Stochastic CT Reconstruction Based on Particle Swarm Optimization for Limited-Angle Sparse Projection Data[J]. Acta Optica Sinica, 2018, 38(1): 0111003

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    Paper Information

    Category: Imaging Systems

    Received: Jul. 19, 2017

    Accepted: --

    Published Online: Oct. 22, 2018

    The Author Email: Luo Yinghao (luoinghao＠gmail．com)

    DOI:10.3788/AOS201838.0111003

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology