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Split-Bregman Algorithm with Attenuation Correction for L-Shell Polychromatic X-ray Fluorescence Computed Tomography

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L-shell X-ray fluorescence computed tomography based on polychromatic X-rays is a promising imaging technique for early cancer diagnosis. However, the presence of self-absorption and the long scanning time limit its usage in clinic. In this work, a reconstruction method based on split-Bregman algorithm which used sparseview projection data was proposed. Furthermore, the attenuation effect was also considered in the algorithm. In the attenuation correction, factors including the X-ray energy and the platinum concentration were taken into account. Then weighted factors calculated in the procedure of attenuation correction were added into the contribution function of pixels in the split-Bregman based reconstruction method. In the end, the feasibility of this method was tested using a cylindrical phantom with 8 mm in diameter by the Monte Carlo simulation. The phantom contained four inserts, all of which were 1.5 millimeter in diameter and filled with 0.10%, 0.20%, 0.40% and 0.80% platinum solutions, respectively. The results show that both the contrast-to-noise ratios and lowest detectable sensitivities are improved for the proposed method, comparing to the conventional MLEM. The contrast-to-noise ratios of images reconstructed by our method with 45 projections are already better than that reconstructed by MLEM with 60 projections. When using 60 projections in our method and comparing to 60 projections in the MLEM with correction, the contrast-to-noise ratio of the insert filled with 0.10% platinum solutions increased from 6.49 to 36.90, indicating its high efficiency and robustness.

Keywords: ATTENUATION CORRECTION; L-SHELL XFCT; MONTE CARLO SIMULATION; POLYCHROMATIC; SPARSE-VIEW

Document Type: Research Article

Publication date: 01 March 2020

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  • Journal of Medical Imaging and Health Informatics (JMIHI) is a medium to disseminate novel experimental and theoretical research results in the field of biomedicine, biology, clinical, rehabilitation engineering, medical image processing, bio-computing, D2H2, and other health related areas.
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