• Acta Optica Sinica
  • Vol. 41, Issue 6, 0611003 (2021)
Lei Li1、2, Chuandong Tan1、2, Mingjuan Liao2、3, Haijun Yu2、3, Yarui Xi2、3, and Fenglin Liu1、2、3、*
Author Affiliations
  • 1State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing 400044, China
  • 2Engineering Research Center of Industrial Computed Tomography Nondestructive Testing, Ministry of Education, Chongqing University, Chongqing 400044, China
  • 3Key Laboratory of Optoelectronic Technology & Systems (Chongqing University), Ministry of Education, Chongqing 400044, China;
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    DOI: 10.3788/AOS202141.0611003 Cite this Article Set citation alerts
    Lei Li, Chuandong Tan, Mingjuan Liao, Haijun Yu, Yarui Xi, Fenglin Liu. Analytic Reconstruction for Parallel Translational Computed Tomography Based on Radon Inverse Transform[J]. Acta Optica Sinica, 2021, 41(6): 0611003 Copy Citation Text show less
    Schematic diagram of PTCT scanning mode
    Fig. 1. Schematic diagram of PTCT scanning mode
    Planar geometric model of PTCT
    Fig. 2. Planar geometric model of PTCT
    Geometric model of multi-translation PTCT. (a) 4T geometric model; (b) 6T geometric model
    Fig. 3. Geometric model of multi-translation PTCT. (a) 4T geometric model; (b) 6T geometric model
    Parallel-beam geometric model of the 1T-PTCT
    Fig. 4. Parallel-beam geometric model of the 1T-PTCT
    Fan-beam geometric model of 1T-PTCT
    Fig. 5. Fan-beam geometric model of 1T-PTCT
    Reconstruct the geometric relationship of point M
    Fig. 6. Reconstruct the geometric relationship of point M
    Schematic diagram of nth translation of PTCT coordinate system
    Fig. 7. Schematic diagram of nth translation of PTCT coordinate system
    Reconstruction process by PTCT-DHB algorithm. (a) Original phantom image; (b) image reconstructed from the 1st translation’s projections; (c)--(e) images reconstructed from the 1st-2nd,1st-3rd, and 1st-4th translations’ projections, respectively; (f) final image reconstructed from 5T projections
    Fig. 8. Reconstruction process by PTCT-DHB algorithm. (a) Original phantom image; (b) image reconstructed from the 1st translation’s projections; (c)--(e) images reconstructed from the 1st-2nd,1st-3rd, and 1st-4th translations’ projections, respectively; (f) final image reconstructed from 5T projections
    Images reconstructed by different algorithms. (a) Original phantom image; (b)--(d) images reconstructed by PTCT-SIRT algorithm, PTCT-FBP algorithm, and PTCT-DHB algorithm, respectively; (e)--(h) magnified images of rectangle selected regions of Fig. (a)--(d), respectively
    Fig. 9. Images reconstructed by different algorithms. (a) Original phantom image; (b)--(d) images reconstructed by PTCT-SIRT algorithm, PTCT-FBP algorithm, and PTCT-DHB algorithm, respectively; (e)--(h) magnified images of rectangle selected regions of Fig. (a)--(d), respectively
    Profiles along the horizontal center of images reconstructed by different algorithms
    Fig. 10. Profiles along the horizontal center of images reconstructed by different algorithms
    Experimental system of PTCT
    Fig. 11. Experimental system of PTCT
    Images reconstructed by different algorithms. (a) PTCT-SIRT algorithm; (b) PTCT-FBP algorithm; (c) PTCT-DHB algorithm; (d)--(f) magnified images of rectangle selected regions of Fig. (a)--(c), respectively
    Fig. 12. Images reconstructed by different algorithms. (a) PTCT-SIRT algorithm; (b) PTCT-FBP algorithm; (c) PTCT-DHB algorithm; (d)--(f) magnified images of rectangle selected regions of Fig. (a)--(c), respectively
    Amplitude-frequency characteristics of derivation operation and backward difference operation
    Fig. 13. Amplitude-frequency characteristics of derivation operation and backward difference operation
    ParameterValue
    Scanning model5T-PTCT
    Sampling modelEqual-angular
    Number of samples per translation100
    Source to object distance D /mm75
    Source to detector distance L /mm225
    Detector array length /pixel1000
    Detector pixel size /mm0.1
    Reconstruction matrix /(pixel×pixel)512×512
    Table 1. Parameters of numerical simulations
    ItemPTCT-SIRTPTCT-FBPPTCT-DHB
    RMSE0.01580.02700.0162
    PSNR36.032331.368135.8051
    SSIM0.99780.99360.9977
    Table 2. Quantitative metrics of images reconstructed by different algorithms
    ParameterValue
    Scanning model7T-PTCT
    Sampling modelEqual-spatial
    Number of samples per translation100
    Source to object distance D /mm80.3
    Source to detector distance L /mm259.6
    Detector array length /pixel1536
    Detector pixel size /mm0.085
    Reconstruction matrix /(pixel×pixel)512×512
    Number of iterations500
    Tube voltage /kV100
    Tube current /μA83
    Table 3. Parameters of the practical experiment
    Lei Li, Chuandong Tan, Mingjuan Liao, Haijun Yu, Yarui Xi, Fenglin Liu. Analytic Reconstruction for Parallel Translational Computed Tomography Based on Radon Inverse Transform[J]. Acta Optica Sinica, 2021, 41(6): 0611003
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