• Acta Optica Sinica
  • Vol. 38, Issue 11, 1111002 (2018)
Peijun Chen1、*, Peng Feng1、2、*, Weiwen Wu1、3, Xiaochuan Wu1, Xiang Fu1, Biao Wei1, and Peng He1、2、*
Author Affiliations
  • 1 Key Laboratory of Optoelectronic Technology and Systems of the Education Ministry of China, Chongqing University, Chongqing 400044, China
  • 2 Collaborative Innovation Center for Brain Science, Chongqing University, Chongqing 400044, China
  • 3 University of Massachusetts Lowell, Lowell, Massachusetts 0 1854, USA
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    DOI: 10.3788/AOS201838.1111002 Cite this Article Set citation alerts
    Peijun Chen, Peng Feng, Weiwen Wu, Xiaochuan Wu, Xiang Fu, Biao Wei, Peng He. Material Discrimination by Multi-Spectral CT Based on Image Total Variation and Tensor Dictionary[J]. Acta Optica Sinica, 2018, 38(11): 1111002 Copy Citation Text show less
    Mouse thorax phantom after addition of iodine contrast agent (first channel)
    Fig. 1. Mouse thorax phantom after addition of iodine contrast agent (first channel)
    Image reconstruction results of mouse thorax phantom by different algorithms in different energy channels
    Fig. 2. Image reconstruction results of mouse thorax phantom by different algorithms in different energy channels
    Quantitative evaluation of image reconstruction results of mouse thorax phantom. (a) RMSE; (b) SSIM; (c) FSIM
    Fig. 3. Quantitative evaluation of image reconstruction results of mouse thorax phantom. (a) RMSE; (b) SSIM; (c) FSIM
    Mean values and corresponding relative biases of linear attenuation coefficient for iodine contrast agent, soft issue and bone. (a)(d) Iodine contrast agent; (b)(e) soft issue; (c)(f) bone
    Fig. 4. Mean values and corresponding relative biases of linear attenuation coefficient for iodine contrast agent, soft issue and bone. (a)(d) Iodine contrast agent; (b)(e) soft issue; (c)(f) bone
    Material decomposition of reconstruction results obtained by different algorithms. (a) Bone; (b) soft issue; (c) iodine contrast agent; (d) color images after blending
    Fig. 5. Material decomposition of reconstruction results obtained by different algorithms. (a) Bone; (b) soft issue; (c) iodine contrast agent; (d) color images after blending
    Convergence of average RMSE
    Fig. 6. Convergence of average RMSE
    Peijun Chen, Peng Feng, Weiwen Wu, Xiaochuan Wu, Xiang Fu, Biao Wei, Peng He. Material Discrimination by Multi-Spectral CT Based on Image Total Variation and Tensor Dictionary[J]. Acta Optica Sinica, 2018, 38(11): 1111002
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