Laser & Optoelectronics Progress, Volume. 61, Issue 18, 1811001(2024)
Deep-Learning-Based Self-Absorption Correction for Fan Beam X-Ray Fluorescence Computed Tomography
Fig. 2. Projected sinograms. (a) Sinogram with absorption; (b) sinogram without absorption
Fig. 5. Comparison of the projected sinograms. (a) (b) (c) Original sinograms; (d) (e) (f) corrected sinograms; (g) (h) (i) objective sinograms
Fig. 6. Comparison of reconstructed images of the projected sinograms. (a) (b) (c) Reconstructed original sinograms; (d) (e) (f) reconstructed corrected sinograms; (g) (h) (i) reconstructed objective sinograms
Fig. 11. Reconstructed images. (a) Uncorrected reconstructed image; (b) corrected reconstructed image
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Mengying Sun, Shanghai Jiang, Xiangpeng Li, Xin Huang, Bin Tang, Xinyu Hu, Binbin Luo, Shenghui Shi, Mingfu Zhao, Mi Zhou. Deep-Learning-Based Self-Absorption Correction for Fan Beam X-Ray Fluorescence Computed Tomography[J]. Laser & Optoelectronics Progress, 2024, 61(18): 1811001
Category: Imaging Systems
Received: Dec. 29, 2023
Accepted: Jan. 22, 2024
Published Online: Sep. 14, 2024
The Author Email: Shanghai Jiang (jiangshanghai@cqut.edu.cn), Xinyu Hu (hxy_dz@cqut.edu.cn)
CSTR:32186.14.LOP232787